Identifying fonts from HTML

# Web Search Results for "Tinker Thinking Machines font family aura design system"

## 1. Typography - Cognite Docs
URL: https://docs.cognite.com/aura-design-system/foundations/typography

> Aura typefaces, type scale, and how typography tokens map to Inter and Source Code Pro.
...
Typography is foundational to creating clear, consistent, and accessible interfaces. Our system uses design tokens and a well-defined set of styles to ensure type is applied consistently across products, platforms, and teams.
...
Typography tokens are predefined values that represent font properties like font family, size, weight, letter spacing and line height. Rather than using arbitrary values (e.g., setting font-size: 17px), tokens standardize how typography is applied across components and layouts.
...
- Ensures consistency and scalability across the design system
- Makes it easier to implement updates or refinements system-wide
- Supports design–developer alignment through shared, meaningful naming conventions
...
## Typefaces
...
| Token | Font | Use |
| --- | --- | --- |
| `--font-sans` / `--font-inter` | Inter | Main product copy — UI text, labels, and dense interfaces |
| `--font-mono` | Source Code Pro | Code blocks, technical strings, terminal output |
...
## Type scale
...
Styles are grouped by role: Text for product UI copy and Code for monospace technical content.
...
Inter — main product typography.
...
Source Code Pro — code blocks, snippets, and technical strings.

## 2. Tinker - Thinking Machines Lab
URL: https://thinkingmachines.ai/tinker/

Tinker - Thinking Machines Lab
...
### THINKING MACHINES

## 3. Taste - Aura Design System
URL: https://auradesignsystem.com/docs/taste

Taste - Aura Design System
...
Discover the design tokens for spacing, colors, and typography that define the Aura aesthetic.
...
The following sections outline our approach to foundational design tokens that give Aura its distinct identity.
...
@theme inline {
  --spacing: 13px;
...
--font-sans: Inter, sans-serif;
  --info: #e8ebfe;
  --info-contrast: #0927ec;
  --success: #e8fef7;
  --success-contrast: #
...
45d3c;
  --danger: #feefe8;
  --danger-contrast
...
#8e3106;
  --warning: #fefbe8;
  --warning-contrast:
...
5d510
...
;
  --radius-sm: calc(var(--spacing
...
5);
...
calc(var(--
...
* 1);
...
lg: calc(var(--spacing
...
1.5);
...
--radius-xl
...
calc(var(--
...
--aura
...
-contrast: var(--
...
ff;
  --gray-a4: #d7e4ff;
  --gray-a5: #ccdcff;
  --gray-a6: #c2d4ff;
  --gray-a7: #b4c8ff;
  --gray-a8: #99b3ff;
  --gray-a9: #0029b791;
  --gray-a10: #0025a19a;
  --gray-a11: #021a72b4;
  --gray-a12: #000a3aed;

  --gray-contrast: #ffffff;
  --gray-surface: #ffffffcc;
  --gray-indicator: #6d84d5;
  --gray-track: #6d84d5;

  --primary: var(--accent-9);
  --primary-foreground: var(--accent-contrast);
  --secundary: var(--accent-8);
  --secundary-foreground: var(--accent-contrast);

  /* Aura Design System - Root Tokens */
  --aura: 13px;
  --aura-font-stack: "Inter", -apple-system, BlinkMacSystemFont, "Segoe UI",
    "Roboto", "Oxygen", "Ubuntu", "Cantarell", "Fira Sans", "Droid Sans",
    "Helvetica Neue", sans-serif;
  --aura-font-quotes: serif;

  /* Aura Background & Text - Mapped to gray scale */
  --aura-bg: var(--gray-1);
  --aura-text-primary: var(--accent-12);
  --aura-text-primary-inverse: var(--gray-contrast);

  --aura-accents-primary: var(--accent-9);
  --aura-accents-secondary: var(--accent-9);

  /* Aura Component Tokens - Mapped to 12-step system */
  --aura-input-radius: 6.5px;
  --aura-button-radius: 6.5px;
  --aura-input-bg: var(--accent-2);
  --aura-input-placeholder-color: var(--gray-11);
  --aura-radius: 0.5rem;
  --aura-opacity: 0.5;
  --aura-outli...

## 4. tinker.com Design Tokens - Colors, Fonts & CSS | FontOfWeb
URL: https://www.fontofweb.com/tokens/tinker.com

tinker.com Design Tokens - Colors, Fonts & CSS | FontOfWeb
...
Fonts, colors, and design tokens of
...
# tinker.com
...
Foundation: Radius
...
### What is the tinker.com design system?
...
The tinker.com design system includes 30 extracted brand colors, 1 typography styles, and various CSS design tokens used across 7 analyzed pages.
...
### How many colors does tinker
...
com use?
...
tinker.com uses approximately 30 distinct colors across its web properties. These include primary brand colors, neutral palettes, and semantic colors extracted from stylesheets.

## 5. docs/brand/DESIGN_SYSTEM.md
URL: https://github.com/Josue19-08/Aura/blob/main/docs/brand/DESIGN_SYSTEM.md

### Font Families
...
```css
/* Display - Headlines & Titles */
font-family: 'Space Grotesk', sans-serif;
font-weight: 700 (Bold), 600 (Semi-bold);
...
/* Interface - UI Elements & Body */
font-family: 'DM Sans', sans-serif;
font-weight: 400 (Regular), 500 (Medium), 600 (Semi-bold);
...
/* Monospace - Code, Stats, Technical */
font-family: 'IBM Plex Mono', monospace;
font-weight: 500 (Medium);
```

## 6. Tinker - Tinker Documentation
URL: https://tinker-docs.thinkingmachines.ai/

Tinker - Tinker Documentation
...
## Train LLMs withthe Tinker API
...
A cloud training API that gives you full control over your data, algorithms, and models. Write training loops locally — Tinker handles the GPUs.

## 7. thinking-machines-lab/tinker
URL: https://github.com/thinking-machines-lab/tinker

# Repository: thinking-machines-lab/tinker
...
Training API and CLI
...
---

 Tinker Python SDK 
 
 

Documentation:
 tinker-docs.thinkingmachines.ai

## 8. Typography
URL: https://tink.com/brand/our-identity/visual-identity/typography

Lota Grotesque is a typeface that reflects the values of our brand and is part of the Tink personality. It is available in a wide range of weights and styles, but in order to keep things simple and consistent Tink uses three of these.
...
## Three weights
...
HeadlinesLota Grotesque Bold
...
Sub-headlinesLota Grotesque SemiBold
...
Body copyLota Grotesque Regular
...
Strive for a few sizes in the same layout, ideally never more than three. Use sizes evenly divisible by four.
...
Grids and columns help us create dynamic and asymmetric compositions.
...
## Fallback typography
...
In instances such as Google Slides, where Lota is not applicable we use Helvetica Neue.
...
Helvetica Neue Bold Helvetica Neue Regular

## 9. NBC Tinker | Capacity Studios
URL: https://capacity.gg/project/nbc-tinker/

NBC Universal : Bespoke Typeface
...
Some of the things we value most as a boutique studio are our range of creative specialties and our personalized, super-customized approach to each project. We were thrilled to have a chance to flex some of our typographic muscles for this bespoke type family that we designed exclusively for NBC, which also includes some fun little custom features that we built into the working fonts.
...
Capacity StudiosClient: NBC UniversalProject focus: type design + font creation

## 10. Tinker Sans - Laura Meseguer Studio
URL: https://www.laurameseguer.com/case/tinkersans-kent-custom-typeface-sans-serif-branding/

A custom typeface typeface family for the branding of KENT, an American brand of cigarrettes.
...
Tinker Sans is a contemporary sans-serif typeface family inspired by the KENT logo’s four letters. It artfully merges the timeless aesthetics of a classic geometric sans-serif with a twist that embraces beauty in evolution. This meticulously crafted typeface family embodies the intersection of design and technology, where beauty thrives. These complementary aspects synergize, blurring the lines between aesthetics and purpose. Featuring three weights and two sets of alternate characters, Tinker Sans adds layers to packaging and will serve for the brand communication at a global level, enhancing their visual appeal and giving more layers to the packaging and communication campaigns.

# Web Search Results for "thinkingmachines.ai Tinker font sans mono"

## 1. Tinker - Thinking Machines Lab
URL: https://thinkingmachines.ai/tinker/

Tinker - Thinking Machines Lab
...
# Tinker is a training API for researchers
...
## Supported models
...
### THINKING MACHINES

## 2. Tinker: a training API for researchers and developers - Tinker Documentation
URL: https://tinker-docs.thinkingmachines.ai/tinker/

Tinker: a training API for researchers and developers - Tinker Documentation
...
# Tinker: a training API for researchers and developers
...
Tinker lets you focus on what matters in LLM post-training — your data and algorithms — while we handle the heavy lifting of distributed training.
...
You write a simple loop that runs on your CPU-only machine, including the data or environment and the loss function. We figure out how to make the training work on a bunch of GPUs, doing the exact computation you specified, efficiently. To change the model you're working with, you only need to change a single string in your code.
...
Tinker gives you full control over the training loop and all the algorithmic details. It's not a magic black box that makes fine-tuning "easy". It's a clean abstraction that shields you from the complexity of distributed training while preserving your control.

## 3. thinking-machines-lab/tinker
URL: https://github.com/thinking-machines-lab/tinker

# Repository: thinking-machines-lab/tinker
...
Training API and CLI
...
---

 Tinker Python SDK 
 
 

Documentation:
 tinker-docs.thinkingmachines.ai

## 4. Get Started - Tinker Documentation
URL: https://tinker-docs.thinkingmachines.ai/tinker/quickstart/

Get Started - Tinker Documentation
...
# Quick Start
...
This gives you the Python SDK (`import tinker`) and the CLI (`tinker run list`,`tinker checkpoint download`).
...
This page walks through the two main LLM fine-tuning workflows — supervised fine-tuning (SFT) and reinforcement learning (RL) — showing how each step maps to Tinker SDK calls.
...
## API Cheatsheet
...
# Entry point — reads TINKER_API_KEY from environment
service_client = tinker.ServiceClient()
...
# Training client (LoRA fine-tuning)
training_client = service_client.create_lora_training_client(
    base_model="Qwen/Qwen3-8B", rank=32
)
...
# Sampling client (text generation)
sampling_client = service_client.create_sampling_client(
    base_model="Qwen/Qwen3-8B"
)
...
# Tokenizer
tokenizer
...
training_client.get_tokenizer
...
`SamplingClient` is picklable — you can pass it to other
...
for parallel sampling. If your training loop has CPU-heavy work (grading, environment logic), set
...
TINKER_SUB
...
_SAMPLING
...
1` to
...
sample()` and`compute_logprobs()` in a
...
, preventing GIL contention.

## 5. tinker v0.23.0
URL: https://pypi.org/project/tinker/

# tinker v0.23.0
...
The official Python SDK for the tinker API
...
- Email: Tinker authors <tinker@thinkingmachines.ai>
- License: Apache-2.0
- Python: >=3.11
- Keywords: machine learning, tinker
- PyPI: https://pypi.org/project/tinker/
...
- Documentation: https://tinker-docs.thinkingmachines.ai/
- Homepage: https://thinkingmachines.ai/tinker
- Repository: https://github.com/thinking-machines-lab/tinker
...
## Readme

 Tinker Python SDK 
 
 

Documentation:
 tinker-docs.thinkingmachines.ai 
 

## Dependencies

## 6. thinking-machines-lab/tinker-cookbook
URL: https://github.com/thinking-machines-lab/tinker-cookbook/

- `tinker` is a training SDK for researchers and developers to fine-tune language models. You send API requests to us and we handle the complexities of distributed training.
- `tinker-cookbook` includes realistic examples of fine-tuning language models. It builds on the Tinker API and provides common abstractions to fine-tune language models.
...
Here we introduce a few Tinker primitives — the basic components to fine-tune LLMs (see the [quickstart guide](https://tinker-docs.thinkingmachines.ai/tinker/quickstart/) for more details):
...
### Tinker Cookbook
...
Besides these primitives, we also offer **Tinker Cookbook** (a.k.a. this repo), a library of a wide range of abstractions to help you customize training environments.
...
[`tinker_cookbook/recipes/sl_basic.py`](tinker_cookbook/recipes/sl_basic.py) and [`tinker_cookbook/recipes/rl_basic.py`](tinker_cookbook/recipes/rl_basic.py) contain minimal examples to configure supervised learning and reinforcement learning.
...
We also include more complete examples in the [`tinker_cookbook/recipes/`](tinker_cookbook/recipes/) folder:
...
](tinker
...
tinker_
...
The [recipes README](tinker_cookbook/recipes/README.md) covers all available recipes, including Harbor RL, rubric-based grading, VLM classification, and SDFT. Each recipe includes a `README.md` with implementation details, launch commands, and expected results.
...
For the full Tinker documentation, visit [tinker-docs.thinkingmachines.ai](https://tinker-docs.thinkingmachines.ai).

## 7. 101: Hello Tinker - Tinker Documentation
URL: https://tinker-docs.thinkingmachines.ai/tutorials/basics/hello-tinker/

101: Hello Tinker - Tinker Documentation
...
101:
...
Tinker is a remote GPU service for LLM training and inference. You write training loops in Python on your local machine; Tinker executes the heavy GPU operations (forward passes, backpropagation, sampling) on remote workers.
...
## The client hierarchy
...
The entry point to Tinker is the ServiceClient. From it, you create specialized clients:
...
- SamplingClient -- generates text from a model (inference)
- TrainingClient -- runs forward/backward passes and optimizer steps (training)
...
## Sampling from a model
...
Let's create a SamplingClient to generate text. We will use`Qwen/Qwen3.5-9B-Base`, a base (non-chat-tuned) model, so we can feed it raw tokens and get a plain text completion -- no chat template required.
...
Create a`SamplingClient` with a base model name
...
Encode your prompt into tokens using the model's tokenizer
...
Call`sample()` with the prompt and sampling parameters
...
returned tokens back into text
...
## What about training?
...
So far we have only done inference. The real power of Tinker is training -- running forward/backward passes and optimizer steps on remote GPUs while you control the training loop locally.
...
The workflow looks like this:
...
1. Create a TrainingClient with`service_client.create_lora_training_client()`
2. Prepare training data as`Datum` objects (input tokens + loss targets)
3. Call`training_client.forward_backward()` to compute gradients
4. Call`training_client.optim_step()` to update weights
5. Save weights and create a SamplingClient to evaluate the trained model

## 8. Tutorials - Tinker Documentation
URL: https://tinker-docs.thinkingmachines.ai/tutorials/

Tutorials - Tinker Documentation
...
A progressive learning path from first API call to advanced training techniques. All tutorials are marimo notebooks — reactive Python notebooks stored as`.py` files. Read them here or run them interactively.
...
Install the SDK together with the cookbook's`[tutorials]` extra, then set your API key:
...
The`[tutorials]` extra pulls in`marimo`(to open the notebooks),`matplotlib`(for the loss-curve plots in a few tutorials), and the`[math-rl]` dependencies (`sympy`,`pylatexenc`,`math-verify`) that some RL tutorials import.
...
Clone the cookbook and open any notebook in marimo's interactive editor:
...
```
git clone https://github.com/thinking-machines-lab/tinker-cookbook.git
cd tinker-cookbook
marimo edit tutorials/101_hello_tinker.py
...
You can also
...
the notebooks online in molab without installing anything — the cookbook tutorials README links each notebook to its
...
ab launcher.
...
Run the tutorials against a recent cookbook that matches them — an editable clone of`main` or a nightly build. Stable PyPI`tinker-
...
` paired with newer tutorial files can drift.

## 9. Changelog - Tinker Documentation
URL: https://tinker-docs.thinkingmachines.ai/changelog/

Changelog - Tinker Documentation
...
Notable updates to the Tinker SDK, the Tinker Cookbook, and the Tinker Console. SDK and Cookbook entries are dated by PyPI release, Console entries by launch date. For model availability and retirements, see Models & Pricing and Model Deprecations.

## 10. Tinker: General Availability and Vision Input - Thinking Machines Lab
URL: https://thinkingmachines.ai/news/tinker-general-availability/

Tinker: General Availability and Vision Input - Thinking Machines Lab
...
# Tinker: General Availability and Vision Input
...
The waitlist is over! Everybody can use Tinker now; sign up here to get started. See the Tinker homepage for available models and pricing, and check out the Tinker cookbook for code examples.
...
We’ve added two vision models to Tinker: Qwen3-VL-30B-A3B-Instruct and Qwen3-VL-235B-A22B-Instruct. With these, users can process pictures, screenshots, and diagrams for a variety of applications.

# Web Search Results for ""root-CkN1nwxO.css""

## 1. Design system reference | Root developer documentation
URL: https://docs.rootapp.com/docs/app-docs/develop/client/design-system-reference/

Style your apps to match the Root visual style using CSS color variables, spacing, typography, and component patterns provided by the Root SDK.
...
The Root design system is a set of CSS custom properties (variables) prefixed with`--rootsdk-` that the Root hosting environment injects into your App's client at runtime, plus conventions for spacing, radii, typography, shadows, and component patterns that match Root's first-party UI.
...
The CSS variables hold the current theme's color values, allowing your App to automatically adapt when the user switches between light and dark mode. Root updates the variables automatically when the theme changes, so your App does not need to know the actual color values. Just reference the variables and they will adapt.
...
| Token | CSS Variable | Description |
| --- | --- | --- |
| brandPrimary | `--rootsdk-brand-primary` | Primary brand color, used for primary buttons and key interactive elements |
| brandSecondary | `--rootsdk-brand-secondary` | Secondary brand color, used for success states and accents |
| brandTertiary | `--rootsdk-brand-tertiary` | Tertiary brand color, used for additional accents |
...
| Token | CSS Variable | Description |
| --- | --- | --- |
| textPrimary | `--rootsdk-text-primary` | Primary text color for headings and body text |
| textSecondary | `--rootsdk-text-secondary` | Secondary text color for less prominent text |
| textTertiary | `--rootsdk-text-tertiary` | Tertiary text color for disabled or placeholder text |
| textWhite | `--rootsdk-text-white` | White text color, used on dark backgrounds regardless of theme |
...
| Token | CSS Variable | Description |
| --- | --- | --- |
| backgroundPrimary | `--rootsdk-background-primary` | Primary background color
...
main content areas |
| backgroundSecondary | `--rootsdk-background-secondary` | Secondary background color for cards and panels |
| backgroundTertiary | `--rootsdk-background-tertiary` | Tertiary background color
...
nested elements and dropdow...

## 2. rootcf/rootie-css
URL: https://github.com/rootcf/rootie-css

A static css file to use in every web project.
...
# rootie-css
...
A static css file to use in every web project. 
You can use this link to add rootie-css to your project; 
 https://raw.githack.com/rootcf/rootie-css/main/rootie-.css 
 

# Documentation

## 3. CssVarsRoot should be respected in @layer reset, base and tokens to prevent global style leakage
URL: https://github.com/chakra-ui/chakra-ui/issues/9256

# CssVarsRoot should be respected in @layer reset, base and tokens to prevent global style leakage
...
I am using Chakra-ui in a subsystem as part of a huge project. By default, Chakra overrides some of the global styles, so I tried the solution mentioned in [#2145](https://github.com/chakra-ui/chakra-ui/issues/2145), using shadow dom and `CacheProvider`. 
 
However, some Chakra styles do not inherit correctly. After investigating for days, I found the following rules to be involved: 
 
| css layer | rule(selector) | configuration entry to override | file | 
| ------- | --------------------------- | ------------------------------- | ------------------------------- | 
| @reset | html | preflight: {scope: ...} | (not found, possibly in panda css) | 
| @base | html | delete defaultConfig.globalCss.html; globalCss:{xxx:{...}} | `packages/react/src/theme/global-css.ts` | 
| @tokens | :where(html,.chakra-themes) | cssVarsRoot | `packages/react/src/theme/index.ts` | 
| @tokens | :root, .light | condition:{light:...} | `packages/react/src/preset-base.ts` | 
 
Overriding the above configuration entries will fix most of them: 
```typescript
const myCssVarsRoot = ":host";
const config = defineConfig({
  cssVarsRoot: myCssVarsRoot,
  conditions: {
    light: `${myCssVarsRoot}, .light`,
  },
  preflight: { scope: myCssVarsRoot },
  globalCss: {
    [myCssVarsRoot]: defaultConfig.globalCss.html,
  },
});
const system = createSystem(defaultConfig, config);
```
 
In this way we can prevent Chakra styles from leaking without shadow dom by setting `myCssVarsRoot` to the target element. A full implementation of this `ContainedProvider` is available in this [codesandbox](https://codesandbox.io/p/sandbox/wispy-leaf-h99sgr) (and `ShadowProvider` if shadow dom is still needed). 
 
(Note: Drawer and Dialog use a built-in portal that defaults to `docuemnt.body`. To use it in a contained situation, either set `portalled={false}` on `DrawerContent` or specify `portalRef` manuall...

## 4. 37dece8 perf(css): merge top-level :root blocks in built component CSS
URL: https://github.com/core-ds/core-components/commit/37dece8a98ea024e39191782a7fee78d55c119eb

# 37dece8 perf(css): merge top-level :root blocks in built component CSS
...
perf(css): merge top-level :root blocks in built component CSS
...
Each component inlines base tokens plus its own aliases as separate :root
blocks, so a consumer's bundled CSS ends up with hundreds of :root blocks.
They inherit into every node, and Chrome DevTools re-renders each one per
selected/hovered node, freezing the Styles panel (matches primevue#8309).
...
Add a postcss-merge-roots plugin (next to postcss-remove-empty-root) that
collapses all top-level :root rules in each emitted file into one deduped
block, preserving source order so no resolved value changes. Cuts per-file
:root blocks (e.g. button 21 -> 9). Top-level only; @media-scoped :root is
left intact. Applies to every build variant via the shared postcss chain.

## 5. ckeditor5.css | Documentation
URL: https://docs.backdropcms.org/api/backdrop/core%21modules%21ckeditor5%21lib%21ckeditor5%21dist%21browser%21ckeditor5.css/1

-focus:#6cb5f9;--ck-color-base-text:#333;--ck-color-base-active:#2977ff;--ck-color-base-active-focus:#0d65ff;--ck-color-base-error:#db3700;--ck-color-focus-border-coordinates:218, 81.8%, 56.9%;--ck-color-focus-border:hsl(var(--ck-color-focus-border-coordinates));--ck-color-focus-outer-shadow:#cae1fc;--ck-color-focus-disabled-shadow:#77baf84d;--ck-color-focus-error-shadow:#ff401f4d;--ck-color-text:var(--ck-color-base-text);--ck-color-shadow-drop:#00000026;--ck-color-shadow-drop-active:#0003;--ck-color-shadow-inner:#0000001a;--ck-color-button-default-background:transparent;--ck-color-button-default-hover-background:#f0f0f0;--ck-color-button-default-active-background:#f0f0f0;--ck-color-button-default-disabled-background:transparent;--ck-color-button-on-background:#f0f7ff;--ck-color-button-on-hover-background:#dbecff;--ck-color-button-on-active-background:#dbecff;--ck-color-button-on-disabled-background:#f0f2f4;--ck-color-button-on-color:#2977ff;--ck-color-button-action-background:var(--ck-color-base-action);--ck-color-button-action-hover-background:#4d9d30;--ck-color-button-action-active-background:#4d9d30;--ck-color-button-action-disabled-background:#7ec365;--ck-color-button-action-text:var(--ck-color-base-background);--ck-color-button-save:#008a00;--ck-color-button-cancel:#db3700;--ck-color-switch-button-off-background:#939393;--ck-color-switch-button-off-hover-background:#7d7d7d;--ck-color-switch-button-on-background:var(--ck-color-button-action-background);--ck-color-switch-button-on-hover-background:#4d9d30;--ck-color-switch-button-inner-background:var(--ck-color-base-background);--ck-color-switch-button-inner-shadow:#0000001a;--ck-color-dropdown-panel-background:var(--ck-color-base-background);--ck-color-dropdown-panel-border:var(--ck-color-base-border);--ck-color-dialog-background:var(--ck-custom-background);--ck-color-dialog-form-header-border:var(--ck-custom-border);--ck-color-input-background:var(--ck-color-base-background);--ck-color-input-border:var(--ck-co...

## 6. knightedcodemonkey/css
URL: https://github.com/knightedcodemonkey/css/

`@knighted/css` is a bundler-optional CSS pipeline for JavaScript and TypeScript projects. Use it standalone or plug it into your bundler via the `?knighted-css` loader query—it walks the graph, compiles every CSS-like dependency (CSS, Sass/SCSS, Less, vanilla-extract), and hands back both a concatenated stylesheet string and optional `.knighted-css.*` selector manifests for type-safe loaders.
...
- **Graph walking**: Follows `import` trees the same way Node does (tsconfig `paths`, package `exports`/`imports`, hash specifiers, etc.) using [`oxc-resolver`](https://github.com/oxc-project/oxc-resolver).
...
- **Multi-dialect compilation**: Runs Sass, Less, Lightning CSS, or vanilla-extract integrations on demand so every dependency ends up as plain CSS.
...
- **Attribute-aware imports**: Honors static `with { type: "css" }
...
gets pulled into
...
when extensions aren’t present.
...
- **Loader + CLI**: Ship CSS at runtime via `?knighted-css` loader queries or ahead of time via the `css()` API and the `knighted-css-generate-types` command.
...
- **Shadow
...
components, or keep
...
—all without wiring
...
| Workspace | NPM Name | What it contains |
| --- | --- | --- |
| `packages/css` | [`@knighted/css`](./packages/css/README.md) | The production library: graph walker, compilation pipeline, loader helpers, CLI, and docs. Published to npm and meant for real builds. |
| `packages/playwright` | [`@knighted/css-playwright-fixture`](./packages/playwright/README.md) | The end-to-end demo + regression suite. Playwright drives Lit + React examples, hash-import workspace scenarios, and SSR checks to ensure
...
core package keeps working across bundlers. |
...
```ts
import { css } from '@knighted/css'
...
const sheet = await css('./src/entry.tsx', {
  cwd: process.cwd(),
  lightningcss: { minify: true },
})

console.log(sheet) // use during SSR, static builds, or to inline Shadow DOM styles
...
- Need runtime imports? See [docs/loader.md](./
...
/loader.md).
- Want strong selecto...

## 7. Index of /files/style
URL: https://root.cern/files/style/

Index of /fi… (9 chars truncated)
… (178 lines truncated)
<truncation_notice>
Full output written to: /var/folders/d9/mzhyr7lx6xbf236j5ll9v_300000gn/T/devin-overflows-501/173d3e20/content.txt
</truncation_notice>

# Web Search Results for ""playground-AlZIgwfc.css""

## 1. CSS Playground — Edit & Test Demos Live | CodeFronts
URL: https://codefronts.com/playground/

CSS Playground — Edit & Test Demos Live | CodeFronts
...
# CSS Playground — Edit, Test, and Style Demos Live
...
A free browser-based CSS playground — pick a curated demo (buttons, cards, forms, loaders), edit HTML, CSS, and JavaScript live in a sandboxed preview, apply one-click variants (darker, lighter, glow, brutalist, glass, neon), run accessibility checks, and copy production-ready code.
...
Live HTML / CSS / JS editor
...
Edit code in tabbed panels and watch the sandboxed iframe preview update instantly. No build step, no setup.
...
Apply darker, lighter, glow, brutalist, glass, or neon transforms to the current CSS — preview, then keep or discard.
...
Every snippet is checked for aria-label coverage, focus state rules, and WCAG colour contrast — issues flagged in real
...
Yes. The playground is completely free with no sign-up, no rate limits, no premium tier, and no tracking. Everything runs in your browser.
...
Your edits run inside a sandboxed iframe in your own browser. Nothing is sent to a server — code never leaves your machine, and your edits are not saved between sessions.
...
Yes. Every demo is pure HTML, CSS, and (optionally) plain JavaScript with no framework dependencies. Click "Copy all" to grab a self-contained snippet you can drop into any project.
...
### What CSS
...
The built-in variants are Darker, Lighter, Glow, Brutalist, Glass, and Neon. Each rewrites the current CSS in place — preview the change, then click Keep to commit or Discard to revert.
...
The checker scans your HTML and CSS for common accessibility issues: missing aria-label on buttons, unlabeled form inputs, decorative SVGs without aria-hidden, missing focus styles, and WCAG AA colour contrast (4.5:1 minimum) between the first two colours in your CSS.
...
No. The playground is intentionally session-only — refreshing the page or selecting a different demo resets the editor. Use "Copy all" to keep your changes.

## 2. CSS Playground
URL: https://www.cssplayground.dev/?lang=en-US

CSS Playground 

Click on each concept to view details and practice

## 3. HTML Playground + CSS Playground + JS Playground
URL: https://code-editor-playground.vercel.app/

HTML Playground + CSS Playground + JS Playground
...
##### ![CSS](https://code-editor-playground.vercel.app/assets/css-bLrZJUBe.png) CSS

## 4. joshwcomeau/playground
URL: https://github.com/joshwcomeau/playground

A simple playground for HTML, CSS and JavaScript supporting module imports.
...
## README

 
 Playground 
 
 A simple playground for HTML, CSS and JavaScript supporting module imports. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

**Playground** is a HTML, CSS and JS demonstration component that runs entirely in the browser and does not require loading any third party sites.
...
```
npm install styled-components @agney/playground
# OR
yarn add styled-components @agney/playground
```
...
Playground uses [styled-components](https://styled-components.com/) for styling.
...
```jsx
import Playground from "@agney/playground";
...
. Allows bare ES package imports
...
can add imports for
...
supports ES Module resolution and
...
| Props | description | default | required |
| :--------------: | :-------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------: | :------: |
| id | a unique identifier for the iFrame | | true |
| initialSnippet | Initial code to be displayed | | true |
| defaultEditorTab | Initial editor tab to be displyed. Possible values: "markup", "css", "javascript" | "markup" | false |
| defaultResultTab | Initial tab on result panel to be displayed. Possible values: "console", "result" | "result" | false |
| transformJs | Transform the JavaScript using Babel. This is required if you want bare module imports | false | false |
| presets | Array of presets you want Babel to transform. This works only if transformJs is true. Eg. `["react", "es2015"]` | | false |
| theme | Pass in the theme variables to customise the appearance | [Our Theme](https://github.com/agneym/playground/blob/master/playground/src/utils/theme.ts) | false |
...
```jsx
import Playground from "@agney/playground";
...
const App = () => {
  const snippet = {
    markup: `<div id=app />`,
    css: ``,
    javascript: `import React, { createElement } from "https://cdn....

## 5. ⚡️ Lightning CSS Playground
URL: https://lightningcss.dev/playground/

⚡️ Lightning CSS Playground
...
⚡️ Lightning CSS Playground
...
# Lightning CSS Playground
...
[ GitHub ](https://github.com/parcel-bundler/lightningcss)
...
Minify CSS modules Analyze dependencies Visitor ### Draft syntax
...
Custom media queries ### Targets
...
Chrome: Firefox: Safari: Opera: Edge: IE: iOS: Android: Samsung:

## 6. Code Playground - HTML CSS and JS Compiler
URL: https://codeplayground.workzio.io/

Code Playground - HTML CSS and JS Compiler

HTML Editor

## 7. cssnext Playground
URL: https://cssnext.github.io/playground/

cssnext Playground
...
/* custom properties */ :root
...
--fontSize: 1rem; --mainColor: #12345678; --highlightColor: hwb(190, 35%, 20%); } /* custom properties set & @apply rule */ :root
...
--centered: { display: flex; align-items: center; justify-content: center; }; } .centered
...
centered; } /* custom media queries */ @custom-media --viewport-medium (width <= 50rem); /* some var() & calc() */ body { color: var(--mainColor); font-size: var(--fontSize); line-height: calc(var(--fontSize) * 1.5); padding: calc((var(--fontSize) / 2) + 1px); } /* custom media query usage */ @media (--viewport-medium) { body { font-size: calc(var(--fontSize) * 1.2); } } /* custom selectors */ @custom-selector :--heading h1, h2, h3, h4, h5, h6; :--heading { margin-top:
...
0 } /* image-set function */ .foo { background-image: image-set( url(img/test.png) 1x, url(img/test-2x.png) 2x ); } /* colors stuff */ a { color: var(--highlightColor); transition
...
autoprefixed
...
{ color: gray(255, 50%)
...
color: rebeccapurple }
...
focus { background-color: rgb(255 153 0 / 33
...
solid hsl(1turn 60% 50
...
: color(var
...
blackness(+20%)) }
...
small-caps
...
lining-nums

## 8. itsjavi/css-grid-playground
URL: https://github.com/itsjavi/css-grid-playground

# Repository: itsjavi/css-grid-playground
...
Interactive CSS Grid Layout tool: Edit, view real-time changes, and share prototypes. Includes some helpful presets to get started.
...
# CSS Grid Playground [![Build Status
...
https://github.com/itsjavi/css-grid-playground/actions/workflows/quality.yml/badge.svg)](https://github.com/itsjavi/css-grid-playground/actions/workflows/quality.yml)
...
**CSS Grid Playground** lets you visually play with the [CSS Grid Layout](https://www.w3.org/TR/css3-grid-layout/)
elements in the browser to quickly sketch up a layout for your site.
...
The layout, which provides a basic way of editing a container and its direct children, renders changes instantly as you
update the corresponding CSS giving you instant feedback.
...
after cloning this repository

## 9. tailwindlabs/tailwindcss-playground
URL: https://www.github.com/tailwindcss/playground

# Tailwind CSS Playground
...
A simple starter project for playing around with Tailwind in a proper PostCSS environment.
...
Building for production
...
Even though this isn't necessarily a starter kit for a proper project, we've included an example of setting up [cssnano](https://cssnano.co/) to optimize your CSS for production.
...
After that's done, check out `./public/build/tailwind.css` to see the optimized output.

## 10. Tailwind CSS Playground
URL: https://tail-wind-css-play-ground.vercel.app/

Tailwind CSS Playground
...
# Tailwind CSS Playground
...
Experiment with Tailwind CSS utility classes and see live results
...
Blue ButtonCard LayoutGradient BackgroundFlex CenterText StylesBorder & Shadow
...
Tailwind Classes
...
BoxButtonText

# Web Search Results for ""tinker-playground-chat-text" font"

## 1. Open Aiplayground Fun Starts
URL: https://chatmemo.com/open-aiplayground-fun-starts

playground and felt like you walked
...
s garage full
...
blinking LEDs and half
...
finished coffee cups? You
...
alone. Unlike the slick,
...
front porch of ChatGPT, the OpenAI Playground is more like the basement lab where
...
real magic—and mess—happens. It
...
’s got sliders for “temperature
...
and “top_p” that sound like they belong on a synth, not
...
AI interface. But
...
kicker: if you
...
thinks, speaks, or even stumbles
...
haiku, the open
...
playground is where
...
god—with parameters.
...
even embeddings—without
...
spicy). You get
...
max tokens, presence penalty, and frequency penalty like you
...
tuning a guitar. Want your
...
to be more creative
...
aiplayground gives you the knobs; you decide
...
Easy as pie: just head to https://platform.openai.com/playground—not chat.openai.com, not some sketchy .net clone, but the real-deal platform subdomain. Log in with your OpenAI account (yes, you still need one), and boom—you’re in. No app install, no CLI, just your browser and curiosity. Pro tip: bookmark it. And maybe clear your cache if it loads slower than a dial-up modem in ‘99. Once inside, you’ll see dropdowns for models, text boxes for prompts, and enough sliders to make a sound engineer jealous. Welcome to the open aiplayground—where prompts become playgrounds.
...
Whether you’re tweakin’ prompts in the open aiplayground or runnin’ models off your laptop, knowledge is your compass. Start by bookmarkin’ the Chat Memo homepage—we drop fresh, no-BS guides every week. Then, wander over to the Explore section for deep dives that don’t kiss corporate boots. And if you’re hungry for more underground tricks, our piece on Open AI GTB Secrets Exposed reveals how power users bend AI to their will—no login required. Because in this wild digital frontier, the best tools aren’t always the shiniest… they’re the freest.
...
The OpenAI Playground is a web-based interface that allows users to interact directly with OpenAI’s language models, adjust parameters like ...

## 2. Chat GPT Playground: A Beginner’s Guide to Creating Your Chatbot
URL: https://supersparrow.org/chat-gpt-playground/

3. Now that you’re connected, it’s time to customize your chatbot. You can start by setting up automated responses for certain keywords or phrases so that when a user types in those particular words or phrases, the bot will respond with an appropriate response. You can also customize conversation topics, adding questions related to what you want your chatbot to discuss with users. Finally, add some personality to your bot by changing its font size and color scheme, as well as any other customizations you’d like it to have.

## 3. How to add a custom prompt before form input? - API - OpenAI Developer Community
URL: https://community.openai.com/t/how-to-add-a-custom-prompt-before-form-input/692623/5

for chat, you have a messages array. You can
...
that array before sending it off to OpenAI.
...
I’ve been playing around with the Vercel SDK and
...
. Specifically,
...
’ve been
...
the chat mode feature
...
Vercel
...
their documentation.
...
’ve been tinkering
...
If you haven’t tried yet, a good testbench to get started is the playground:
...
there you can manually test how well your prompt works.
...
And if you’re a little lost on where to start with prompting, here’s the prompting guide from openai: https://platform.openai.com/docs/guides/prompt-engineering It contains a bunch of basic tricks to help you get started.

## 4. Text Generation Web UI Review: Is This the Easiest Way to Run Local LLMs?
URL: https://sider.ai/blog/ai-tools/text-generation-web-ui-review-is-this-the-easiest-way-to-run-local-llms

If you’ve ever wished you could run GPT‑style models on your own machine—no API keys, no data leaving your desk—there’s a good chance you’ve heard of Text Generation Web UI. It’s a popular, open-source front end that puts a clean, configurable interface on top of powerful local LLM backends like Transformers, llama.cpp, and ExLlama. In this Text Generation Web UI review, we’ll unpack what it does well, where it stumbles, and how it compares to other options—so you can decide if it’s the right cockpit for your local AI setup.
...
Text Generation Web UI (often abbreviated as “TGU” or “textgen webui”) is an open‑source, browser‑based interface for running local large language models. Think of it as an all‑in-one control panel that:
...
* **Exposes a feature‑rich chat and text generation UI** with history, presets, and parameter controls.
...
* **Adds power tools** like LoRA loading, prompt templates, character cards, RAG extensions, and generation streaming.
...
* **Chat and Instruct modes:** Switch between role‑playing or assistant‑style prompting. Character cards and system prompts help simulate personas reliably.
...
* **Parameter panel in plain sight:** Temperature, top‑p, top‑k, repetition penalty, `min\_p`, `typical\_p`, and stop sequences are all one click away. You can save and share presets.
...
Text Generation Web UI is a browser-based interface for running local LLMs. It lets you load models, tweak generation parameters, and chat or generate text privately on your own hardware.

## 5. FastChat Alternatives: Smarter, Simpler Ways to Run Your Own AI Chat
URL: https://sider.ai/blog/ai-tools/fastchat-alternatives-smarter-simpler-ways-to-run-your-own-ai-chat

1. Text-generation web UI and friends: the tinkerers’ playground
...
What it is: GUIs that make running local models feel like a modded video game—sliders for temperature, dropdowns for quant sizes. Not exactly production, but great for learning and spot testing.
...
Best for: Hobbyists, benchmarkers, and “just show me the settings” folks.

## 6. TilmanGriesel/chipper: ✨ AI interface for tinkerers (Ollama, Haystack RA...
URL: http://gitmemories.com/index.php/TilmanGriesel/chipper

Chipper provides a web interface, CLI, and a modular, hackable, and lightweight architecture for RAG pipelines, document splitting, web scraping, and query workflows, enhancing generative AI models with advanced information retrieval capabilities. It can also function as a proxy between an Ollama client, such as Enchanted or Open WebUI, and an Ollama instance. Built with Haystack, Ollama, Hugging Face, Docker, TailwindCSS, and ElasticSearch, it runs as a fully containerized service.
...
This project wants
...
be more than just a technical foundation, for educators, it provides a
...
to teach AI concepts in
...
manageable and practical way.
...
explorers, tinkerers and companies, it offers a
...
upon a versatile
...
Use Chipper's built-in web interface to set up and customize RAG pipelines with ease. Built with vanilla JavaScript and TailwindCSS, it works offline and doesn't require any framework-specific knowledge. Run the`/help` command to learn how to switch models, update the embeddings index, and more.
...
- [x] Mirror Ollama Chat API (Enable Chipper as a drop-in middleware)
- [x] Haystack Chat Generators (`ChatPromptBuilder`&`OllamaChatGenerator`)
- [x] Distributed Processing (Chain multiple Chipper instances for workload distribution)
...
- [ ] React-Based Web Application (Modernized UI/UX)

## 7. Everything About OpenAI's ChatGPT
URL: https://tech-vise.com/about-openais-chatgpt/

ityAI
- For sales and marketing: ChatSpot
- For messaging: Personal AI
- For tinkering: OpenAI playground, DeepAI Chat
- For fun: Character.AI
- For serious: Armageddon (kidding)
- On social media: Snapchat My AI
...
- For learning: Khan Academy
...
s Khanmigo
...
mobile: Chatty Butler, Chat

## 8. What are the Best AI Chatbots in 2024?
URL: https://www.webtechpanda.com/what-are-the-best-ai-chatbots-in-2024/

- Overall Best Chatbot: ChatGPT
- Integration with Google Apps: Google Bard
- Microsoft Bing AI
- Tinkering: OpenAI Playground
- Building Your Chatbot: Zapier AI Chatbot
- Learning: Khan Academy’s Khanmigo
- DeepAI Chat
- Longest Conversation Memory: Claude
- Multiple AI Models: Poe
- Internet Deep Dives: Perplexity
- Content Writing: Jasper Chat,
- Chat by Copy.ai
- Chatsonic
- ZenoChat
- Web Search: YouChat
...
### OpenAI Playground
...
OpenAI’s playground allows you to delve deeper into GPT models beyond simple prompts. It empowers you to adjust various settings:
...
- Temperature influences the unpredictability of the generated text.
- Maximum length determines the size of the output.
- Stop sequences guide the model on when to conclude the text generation.
...
This spot is perfect for exploring what GPT can do. You can try improving your prompts, grasp how AI language models function, or assess whether an AI-powered app idea could work using an OpenAI chatbot. While it’s not exactly like chatting with a chatbot, it’s still pretty user-friendly and accessible.

## 9. Your next deck is one prompt away. And it'll actually look like your brand. | Prompt, Tinker, Innovate | GenEdge | GenEdge
URL: https://genedge.co/newsletter/your-next-deck-is-one-prompt-away

The leading AI tools now have a built-in skill for building PowerPoint files, and for the first time, they work pretty well. Describe your presentation—topic, audience, brand colors, fonts—and they generate a properly structured .pptx you can download directly from the chat or open in Google Slides.
...
The quality depends almost entirely on how much brand context you give upfront. Hex codes instead of color names. The exact font name instead of "something modern." And as much of the copy as you have ready.
...
The prompt below gives you two paths. Path 1 is the fast version—just your colors and font. Path 2 is the full brand brief, which gets you closer on the first try with less cleanup after.
...
Build me a PowerPoint presentation (.pptx) I can download.… (898 chars truncated)
… (13 lines truncated)
<truncation_notice>
Full output written to: /var/folders/d9/mzhyr7lx6xbf236j5ll9v_300000gn/T/devin-overflows-501/012c47e6/content.txt
</truncation_notice>

# Web Search Results for "site:thinkingmachines.ai Tinker console playground"

## 1. Inkling: Our Open-Weights Model - Thinking Machines Lab
URL: https://thinkingmachines.ai/news/introducing-inkling/

[Try on Tinker](https://tinker.thinkingmachines.ai/playground?utm_source=blog&utm_campaign=inkling_model_release) [Model card](https://thinkingmachines.ai/model-card/inkling/) [Hugging Face](https://huggingface.co/thinkingmachines/inkling)
...
We want to make customization accessible for more use cases, so Inkling is available for fine-tuning on Tinker today. Picking the right base model to fine-tune is a qualitative judgment that combines measurable benchmarks with the unique feel of a model that comes from playing with it. To enable the latter we’re adding the Inkling Playground in the Tinker console: a developer-facing interface for chatting with Inkling.

## 2. Changelog - Tinker Documentation
URL: https://tinker-docs.thinkingmachines.ai/changelog/

Notable updates to the Tinker SDK, the Tinker Cookbook, and the Tinker Console. SDK and Cookbook entries are dated by PyPI release, Console entries by launch date. For model availability and retirements, see Models & Pricing and Model Deprecations.
...
| Console | July 6, 2026 | Added a Session Metrics view to every session page, rolling out to all organizations. Time-series panels show what your training and sampling traffic did over time — active sample requests, training utilization, and average training, sampling, and prefill throughput — with drag-to-zoom, a time-range picker, and a plain-language explanation of each metric. Added a Download Perfetto button to the session page that exports the full session timeline as a`.pftrace` you can open at ui.perfetto.dev. The trace goes deeper than the console panels: per-request training and sampling spans, plus counter tracks for concurrency, throughput, per-request sizes, latency percentiles (p50/p90/p99), running totals, and rate-limit events. Re-exporting picks up new session activity. See the session metrics docs for details. |
...
| Console | June 17, 2026 | Reorganized navigation around sessions: the Training Runs list is replaced by a Sessions list (session ID, created time, owner, project — with filtering and pagination), and each session page shows its training runs. Listing is index-backed, so large projects load much faster. |

## 3. Using Inkling - Tinker Documentation
URL: https://tinker-docs.thinkingmachines.ai/cookbook/inkling/

Using Inkling - Tinker Documentation
...
# Using Inkling
...
Inkling is Thinking Machines Lab's model tailored for Tinker. It is a general-purpose model that can code, reason, and call tools. Model effort can be controlled by a float. Image and audio inputs are also supported.
...
Use tml-renderers to construct all of these inputs.
...
Messages can be OpenAI-compatible Cookbook dictionaries or typed`tml_renderers.chat` objects. Use the format that matches your application.
...
Install the Cookbook with the`inkling` extra, which pulls in the`tml_renderers` package that Inkling's renderer and scripts depend on:
...
in your existing
...
We recommend sweeping learning rate and thinking effort to adapt Inkling to your use case. Use sample_reasoning.py to compare standard effort values.
...
The Cookbook selects Inkling's recommended renderer automatically. Each guide links to its corresponding runnable example.
...
- tml-renderers— Message formats, tools, rendering, and training.
- Thinking effort— Effort controls, recommended sweep values, and scaling results.
- Audio and Images— Multimodal input requirements.
- Rendering tutorial— How renderers bridge messages and model tokens.
- Tinker sampling quickstart— The lower-level sampling flow.

## 4. Get Started - Tinker Documentation
URL: https://tinker-docs.thinkingmachines.ai/tinker/quickstart/

Get Started - Tinker Documentation
...
# Quick Start
...
Set your API key (get one from the Tinker Console):
...
```
export TINKER_API_KEY="your-api-key-here"

```
...
This gives you the Python SDK (`import tinker`) and the CLI (`tinker run list`,`tinker checkpoint download`).
...
This page walks through the two main LLM fine-tuning workflows — supervised fine-tuning (SFT) and reinforcement learning (RL) — showing how each step maps to Tinker SDK calls.
...
## API Cheatsheet
...
```
import tinker
from
...
# Entry point — reads TINKER_API_KEY from environment
service_client = tinker.ServiceClient()
...
# Training client (LoRA fine-tuning)
training_client = service_client.create_lora_training_client(
    base_model="Qwen/Qwen3-8B", rank=32
)
...
# Sampling client (text generation)
sampling_client = service_client.create_sampling_client(
    base_model="Qwen/Qwen3-8B"
)
...
# Tokenizer
tokenizer = training_client.get_tokenizer()
...
`SamplingClient` is picklable — you can pass it
...
other processes for parallel sampling. If your training loop has CPU-heavy work (grading, environment logic), set`T
...
ER_SUBPROCESS_SAMPLING=1` to run`sample()` and`compute_logprobs()` in a dedicated subprocess, preventing GIL contention.

## 5. Navigating these docs – Tinker API
URL: https://tinker-docs.thinkingmachines.ai/docs-outline

- Development tips
- Installation explains how to install both`tinker` and`tinker-cookbook`, and points you to the Tinker Console for your API key.

## 6. Tinker - Thinking Machines Lab
URL: https://thinkingmachines.ai/tinker/

Tinker - Thinking Machines Lab
...
# Tinker is a training API for researchers
...
Control every aspect of model training and fine-tuning while we handle the infrastructure.
...
#### Tinker cookbook
...
Explore realistic examples and common abstractions for fine-tuning language models with the Tinker API.
...
Tinker is a flexible API for efficiently fine-tuning open source models with LoRA. It's designed for researchers and developers who want flexibility and full control of their data and algorithms without worrying about infrastructure management.
...
Tinker handles scheduling, tuning, resource management, and infrastructure reliability so you can focus on the training data and algorithms. Behind the scenes, Tinker orchestrates distributed training on powerful GPU clusters for efficient utilization.
...
A dataset of supervised learning examples or reinforcement learning environments. After picking a base model to train on, the Tinker API provides simple functions to compute gradients, update the weights, and sample outputs from the trained model. See our cookbook for examples to get started.

## 7. Session Metrics - Tinker Documentation
URL: https://tinker-docs.thinkingmachines.ai/tinker/session-metrics/

Session metrics provide critical insight into your session's activity, allowing you to monitor usage and debug performance bottlenecks. The Session Metrics view shows exactly what your training and sampling traffic did over time, including throughput, training utilization, and in-flight requests. You can read the summary panels in the console to track general resource utilization, or export the full timeline to Perfetto for a detailed, per-request view.
...
The Session Metrics view in the console.
...
The console panels are a subset of the trace: In-flight sample requests (the console's "Active sample requests"), Training utilization, and the Training, Generation, and Prefill tokens/sec rates. The exported Perfetto trace is a strict superset, adding per-request sizes, latency percentiles, totals, rate-limit events, and the individual request spans.
...
full picture, every request and counter at fine resolution,
...
a Perfetto trace:
...
Open trace file.
...
grouped: Con
...
## Metric Details
...
- In-flight sample requests (`requests`): sampling requests running at each moment (the console's "Active sample requests"). Split by weights version: each colored band is a different generation (e.g. a newer checkpoint), stacking to the total, so you see the checkpoint mix in flight.
...
- Training utilization (`%`): the percentage of wall-clock time the trainer was actively running forward/backward steps in each interval. Intervals are 1 minute long in Perfetto and can be longer in the console. It will not always be 100%; treat any value above 0% as a sign that training work was happening in that interval.
...
- Rate-limit events/sec (`events/s`): how often the session hit a rate or capacity limit, per second.
...
- Training tokens/sec and Generation tokens/sec (`tok/s`): total training and generated tokens per second. Each request's tokens are spread evenly across the time that request was active (from when it started running to when it finished), instead of being credite...

## 8. 504: OpenCode - Tinker Documentation
URL: https://tinker-docs.thinkingmachines.ai/tutorials/deployment/opencode/

504: OpenCode - Tinker Documentation
...
# Coding with a tinker model using OpenCode
...
- A saved Tinker checkpoint (see Weights Management)
- OpenCode installed
- A`TINKER_API_KEY`(get one from the Tinker Console)
...
OpenCode can talk to any OpenAI-compatible endpoint. Tinker exposes one, so you can chat or code with a fine-tuned checkpoint directly from your terminal — no export or download needed.
...
## Step 2: Add a provider to opencode.json
...
Create or edit`opencode.json` in your project root:
...
```
{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "tinker": {
      "env": ["TINKER_API_KEY"],
      "npm": "@ai-sdk/openai-compatible",
      "models": {
        "tinker://YOUR_CHECKPOINT_PATH": {
          "name": "My Fine-Tuned Model",
          "attachment": false,
          "reasoning": true,
          "temperature": true,
          "tool_call": true,
          "cost": { "input": 0, "output": 0 },
          "limit": {
            "context": 262144,
            "output": 8192
          },
          "options": {
            "separate_reasoning": true
          }
        }
      },
      "options": {
        "baseURL": "https://tinker.thinkingmachines.dev/service… (26 chars truncated)
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# Web Search Results for "https://tinker.thinkingmachines.ai playground"

## 1. Inkling: Our open-weights model - Thinking Machines Lab
URL: https://thinkingmachines.ai/news/introducing-inkling/

We want to make customization accessible for more use cases, so Inkling is available for fine-tuning on Tinker today. Picking the right base model to fine-tune is a qualitative judgment that combines measurable benchmarks with the unique feel of a model that comes from playing with it. To enable the latter we’re adding the Inkling Playground in the Tinker console: a developer-facing interface for chatting with Inkling.
...
To get a feel for the model before committing to a run, users can head to the Inkling Playground in the Tinker console. The playground offers a chat interface with integrated agentic web search, free for a limited time.

## 2. Tinker - Thinking Machines Lab
URL: https://thinkingmachines.ai/tinker/

Tinker - Thinking Machines Lab
...
# Tinker is a training API for researchers
...
Control every aspect of model training and fine-tuning while we handle the infrastructure.
...
## Supported models
...
### THINKING MACHINES
...
#### Tinker uses LoRA
...
#### Tinker cookbook
...
Explore realistic examples and common abstractions for fine-tuning language models with the Tinker API.
...
Tinker is a flexible API for efficiently fine-tuning open source models with LoRA. It's designed for researchers and developers who want flexibility and full control of their data and algorithms without worrying about infrastructure management.
...
Tinker handles scheduling, tuning, resource management, and infrastructure reliability so you can focus on the training data and algorithms. Behind the scenes, Tinker orchestrates distributed training on powerful GPU clusters for efficient utilization.
...
A dataset of supervised learning examples or reinforcement learning environments. After picking a base model to train on, the Tinker API provides simple functions to compute gradients, update the weights, and sample outputs from the trained model. See our cookbook for examples to get started.
...
Tinker is currently available for a broad selection of open-source models, ranging from compact models like Qwen3.5-4B to large MoEs like Kimi-K2.6. We plan to expand our model lineup with even more choices soon.

## 3. Tinker - Tinker Documentation
URL: https://tinker-docs.thinkingmachines.ai/

Tinker - Tinker Documentation
...
## Train LLMs withthe Tinker API
...
A cloud training API that gives you full control over your data, algorithms, and models. Write training loops locally — Tinker handles the GPUs.
...
Get Started → Cookbook Tutorials
...
Model-agnostic LoRA training from 1B to 1T+ parameters — dense and MoE architectures, text and vision.
...
SFT, RL (GRPO, PPO), DPO, distillation. Write your own loop or use cookbook abstractions.
...
### Remote GPU Clusters
...
Distributed training via API. Author code on a CPU machine — Tinker runs the compute.
...
### 15+ Recipes
...
End-to-end recipes for math RL, code RL, tool use, multi-agent training, and more.
...
23

Interactive Tutorials

## 4. Get Started - Tinker Documentation
URL: https://tinker-docs.thinkingmachines.ai/tinker/quickstart/

Get Started - Tinker Documentation
...
# Quick Start
...
```
uv pip install tinker
...
Set your API key (get one from the Tinker Console):
...
TINKER_API_KEY="your-api-key-here"
...
This gives you the Python SDK (`import tinker`) and the CLI (`tinker run list`,`tinker checkpoint download`).
...
This page walks through the two main LLM fine-tuning workflows — supervised fine-tuning (SFT) and reinforcement learning (RL) — showing how each step maps to Tinker SDK calls.
...
## Supervised Fine-Tuning (SFT)
...
## Reinforcement Learning (RL)
...
## API Cheatsheet
...
### Create clients
...
# Entry point — reads TINKER_API_KEY from environment
service_client = tinker.ServiceClient()
...
# Training client (LoRA fine-tuning)
training_client = service_client.create_lora_training_client(
    base_model="Qwen/Qwen3-8B", rank=32
)
...
# Sampling client (text generation)
sampling_client = service_client.create_sampling_client(
    base_model="Qwen/Qwen3-8B"
)
...
# Tokenizer
tokenizer = training_client.get_tokenizer()
...
`SamplingClient` is picklable — you can pass it to other processes for parallel sampling. If your training loop has CPU-heavy work (grading, environment logic), set`TINKER_SUBPROCESS_SAMPLING=1` to run`sample()` and`compute_logprobs()` in a dedicated subprocess, preventing GIL contention.
...
### Prepare training data
...
A`Datum` is a single
...
example. It contains
...
tokens, target tokens, and per-token loss weights (0 = ignore, 1 = compute loss).
...
(importance_
...
### Sample text
...
### Compute log-probabilities
...
### Forward-backward
...
### Optimizer step
...
### Save and load weights
...
### Concurrent requests

## 5. OpenAI-Compatible API - Tinker Documentation
URL: https://tinker-docs.thinkingmachines.ai/tinker/compatible-apis/openai/

OpenAI-Compatible API - Tinker Documentation
...
# OpenAI API Compatible Inference (in beta)
...
OpenAI-compatible inference lets you interact with any model checkpoint in Tinker, using an endpoint compatible with the OpenAI Completions API. It’s designed to let you easily “poke at” your model while you're training it.
...
For inference within your training runs (e.g. RL), we recommend using Tinker’s standard sampling client (see the API Reference).
...
Currently, OpenAI-compatible inference is meant for testing and internal use with low internal traffic, rather than large, high-throughput, user-facing deployments. Latency and throughput may vary by model and may change without notice during
...
beta. If you need higher or more stable throughput, contact the Tinker team in our Discord for guidance on larger-scale setups.
...
## Using OpenAI compatible inference from an OpenAI client
...
The new interface exposes an OpenAI-compatible HTTP API. You can use any OpenAI SDK or HTTP client that lets you override the base URL.
...
1. Set the base URL of your OpenAI-compatible client
...
```
https://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1
...
. Use a Tinker sampler weight path as the model name. For example:
...
inker://0034d8c9-0a88-52a9-b2b7-bce7cb1e6fef:train:0/sampler_weights/000080
...
Any valid Tinker sampler checkpoint path works here. You can keep training and sample from the same checkpoint simultaneously.
...
3. Authenticate with your Tinker API key, by passing the same key used for Tinker as the API key to the OpenAI client.
...
Note: We support both`/completions` and`/chat/completions` endpoints. For most use cases we recommend`/chat/completions`. Here's how to decide which one to use:
...
- `/chat/completions`— for chat-formatted prompts. You pass`messages` and the server renders them with the model’s default Hugging Face chat template, so it works out-of-the-box for checkpoints that use that template.
- `/completions`— for raw text continua...

## 6. Using Inkling - Tinker Documentation
URL: https://tinker-docs.thinkingmachines.ai/cookbook/inkling/

Using Inkling
...
# Using Inkling
...
Inkling is Thinking Machines Lab's model tailored for Tinker. It is a general-purpose model that can code, reason, and call tools. Model effort can be controlled by a float. Image and audio inputs are also supported.
...
Use tml-renderers to construct all of these inputs.
...
Messages can be OpenAI-compatible Cookbook dictionaries or typed`tml_renderers.chat` objects. Use the format that matches your application.
...
Install the Cookbook with the`inkling` extra, which pulls in the`tml_renderers` package that Inkling's renderer and scripts depend on:
...
uv pip install 'tinker-cookbook[ink
...
Set the model name in your existing Cookbook workflow:
...
```
model_name = "thinkingmachines/Inkling"
...
We recommend sweeping learning rate and thinking effort to adapt Inkling to your use case. Use sample_reasoning.py to compare standard effort values.
...
The Cookbook selects Inkling's recommended renderer automatically. Each guide links to its corresponding runnable example.
...
- tml-renderers— Message formats, tools, rendering, and training.
- Thinking effort— Effort controls, recommended sweep values, and scaling results.
- Audio and Images— Multimodal input requirements.
- Rendering tutorial— How renderers bridge messages and model tokens.
- Tinker sampling quickstart— The lower-level sampling flow.

## 7. thinking-machines-lab/tinker
URL: https://github.com/thinking-machines-lab/tinker

# Repository: thinking-machines-lab/tinker
...
Training API and CLI
...
---

 Tinker Python SDK 
 
 

Documentation:
 tinker-docs.thinkingmachines.ai

## 8. 101: Hello Tinker - Tinker Documentation
URL: https://tinker-docs.thinkingmachines.ai/tutorials/basics/hello-tinker/

101: Hello Tinker - Tinker Documentation
...
# Tutorial 101: Hello Tinker
...
Tinker is a remote GPU service for LLM training and inference. You write training loops in Python on your local machine; Tinker executes the heavy GPU operations (forward passes, backpropagation, sampling) on remote workers.
...
## The client hierarchy
...
The entry point to Tinker is the ServiceClient. From it, you create specialized clients:
...
- SamplingClient -- generates text from a model (inference)
- TrainingClient -- runs forward/backward passes and optimizer steps (training)
...
Both talk to the same remote GPU workers. Let's start with the ServiceClient.
...
# Create a ServiceClient. This reads TINKER_API_KEY from your environment.
service_client = tinker.ServiceClient()
...
## Sampling from a model
...
Let's create a SamplingClient to generate text. We will use`Qwen/Qwen3.5-9B-Base`, a base (non-chat-tuned) model, so we can feed it raw tokens and get a plain text completion -- no chat template required.
...
The sampling workflow is:
...
1. Create a`SamplingClient` with a base model name
2. Encode your pro… (43 chars truncated)
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format("woff2"),url(/assets/KaTeX_SansSerif-Bold-DbIhKOiC.woff)
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format("woff2"),url(/assets/KaT… (31 chars truncated)
… (247 lines truncated)
<truncation_notice>
Full output written to: /var/folders/d9/mzhyr7lx6xbf236j5ll9v_300000gn/T/devin-overflows-501/f33930d1/content.txt
</truncation_notice>

Found 56 match(es) for pattern 'aura-font' in /var/folders/d9/mzhyr7lx6xbf236j5ll9v_300000gn/T/devin-overflows-501/c35ed2d6/content.txt:
-- 56 matches in /var/folders/d9/mzhyr7lx6xbf236j5ll9v_300000gn/T/devin-overflows-501/c35ed2d6/content.txt
  80|var(--alpha-16);--font-aura:var(--aura-font-family);--font-aura-display:var(--aura-font-display);--f
  81|ont-aura-mono:var(--aura-font-mono);--color-aura-text-default:var(--aura-text-default);--color-aura-
 197|-sm{font-family:var(--aura-font-family);font-size:12px;font-weight:500;line-height:15px}.text-aura-b
 198|tn-md{font-family:var(--aura-font-family);font-size:13px;font-weight:500;line-height:16px}.text-aura
 199|-btn-lg{font-family:var(--aura-font-family);font-size:16px;font-weight:500;line-height:19px}}@layer
1594|ura-large-title-regular{font-family:var(--aura-font-family);font-size:26px;font-weight:400;line-heig
1595|ht:32px}.text-aura-large-title-emphasized{font-family:var(--aura-font-family);font-size:26px;font-we
1596|ight:700;line-height:32px}.text-aura-title-1-regular{font-family:var(--aura-font-family);font-size:2
1597|2px;font-weight:400;line-height:26px}.text-aura-title-1-emphasized{font-family:var(--aura-font-famil
1600|ily:var(--aura-font-family);font-size:17px;font-weight:700;line-height:22px}.text-aura-title-3-regul
1601|ar{font-family:var(--aura-font-family);font-size:15px;font-weight:400;line-height:20px}.text-aura-ti
1602|tle-3-emphasized{font-family:var(--aura-font-family);font-size:15px;font-weight:590;line-height:20px
1603|}.text-aura-headline-regular{font-family:var(--aura-font-family);font-size:13px;font-weight:700;line
1604|-height:16px}.text-aura-headline-emphasized{font-family:var(--aura-font-family);font-size:13px;font-
1605|weight:860;line-height:16px}.text-aura-body-regular{font-family:var(--aura-font-family);font-size:13
1606|px;font-weight:400;line-height:16px}.text-aura-body-emphasized{font-family:var(--aura-font-family);f
1609|var(--aura-font-family);font-size:12px;font-weight:590;line-height:15px}.text-aura-subheadline-regul
1610|ar{font-family:var(--aura-font-family);font-size:11px;font-weight:400;line-height:14px}.text-aura-su
1611|bheadline-emphasized{font-family:var(--aura-font-family);font-size:11px;font-weight:590;line-height:
1612|14px}.text-aura-footnote-regular{font-family:var(--aura-font-family);font-size:10px;font-weight:400;
1613|line-height:13px}.text-aura-footnote-emphasized{font-family:var(--aura-font-family);font-size:10px;f
1614|ont-weight:590;line-height:13px}.text-aura-caption-1-regular{font-family:var(--aura-font-family);fon
1616|gular{font-family:var(--aura-font-family);font-size:10px;font-weight:510;line-height:13px}.text-aura
1617|-caption-2-emphasized{font-family:var(--aura-font-family);font-size:10px;font-weight:590;line-height
1618|:13px}.text-aura-menu-item-regular{font-family:var(--aura-font-family);font-size:13px;font-weight:50
1619|0;line-height:19px}.text-aura-menu-item-emphasized{font-family:var(--aura-font-family);font-size:13p
1620|x;font-weight:590;line-height:19px}.font-aura-root{font-family:var(--aura-font-family)}}@property
1697|0)}:root{--aura-font-family:-apple-system, BlinkMacSystemFont, "SF Pro Text", "SF Pro Display",
1698|"Helvetica Neue", sans-serif;--aura-font-display:-apple-system, BlinkMacSystemFont, "SF Pro
1699|Display", "SF Pro Text", "Helvetica Neue", sans-serif;--aura-font-mono:ui-monospace, "SF Mono",
1702|var(--aura-font-family);--aura-text-large-title-emphasized:700 26px/32px
1703|var(--aura-font-family);--aura-text-title-1-regular:400 22px/26px
1704|var(--aura-font-family);--aura-text-title-1-emphasized:700 22px/26px
1705|var(--aura-font-family);--aura-text-title-2-regular:400 17px/22px
1706|var(--aura-font-family);--aura-text-title-2-emphasized:700 17px/22px
1707|var(--aura-font-family);--aura-text-title-3-regular:400 15px/20px
1708|var(--aura-font-family);--aura-text-title-3-emphasized:590 15px/20px
1709|var(--aura-font-family);--aura-text-headline-regular:700 13px/16px
1710|var(--aura-font-family);--aura-text-headline-emphasized:860 13px/16px
1711|var(--aura-font-family);--aura-text-body-regular:400 13px/16px
1712|var(--aura-font-family);--aura-text-body-emphasized:590 13px/16px
1713|var(--aura-font-family);--aura-text-callout-regular:400 12px/15px
1714|var(--aura-font-family);--aura-text-callout-emphasized:590 12px/15px
1715|var(--aura-font-family);--aura-text-subheadline-regular:400 11px/14px
1716|var(--aura-font-family);--aura-text-subheadline-emphasized:590 11px/14px
1717|var(--aura-font-family);--aura-text-footnote-regular:400 10px/13px
1718|var(--aura-font-family);--aura-text-footnote-emphasized:590 10px/13px
1719|var(--aura-font-family);--aura-text-caption-1-regular:400 10px/13px
1720|var(--aura-font-family);--aura-text-caption-1-emphasized:510 10px/13px
1721|var(--aura-font-family);--aura-text-caption-2-regular:510 10px/13px
1722|var(--aura-font-family);--aura-text-caption-2-emphasized:590 10px/13px
1723|var(--aura-font-family);--aura-text-menu-item-regular:500 13px/19px
1724|var(--aura-font-family);--aura-text-menu-item-emphasized:590 13px/19px
1725|var(--aura-font-family);--aura-text-default:#1a1a1a;--aura-text-secondary:#00000080;--aura-text-tert
1940|var(--aura-font-family);font:var(--tinker-chat-font)}.tinker-playground-chat-transcript{--foreground
1943|var(--aura-font-family);--tinker-chat-content-gap:1rem;--tinker-chat-list-item-gap:.375rem;--tinker-

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1690|0);--destructive:oklch(70.4% .191 22.216);--border:oklch(100% 0 0/.1);--input:oklch(100% 0
1691|0/.15);--ring:oklch(55.6% 0 0);--chart-1:oklch(48.8% .243 264.376);--chart-2:oklch(69.6% .17
1692|162.48);--chart-3:oklch(76.9% .188 70.08);--chart-4:oklch(62.7% .265 303.9);--chart-5:oklch(64.5%
1693|.246 16.439);--sidebar:oklch(20.5% 0 0);--sidebar-foreground:oklch(98.5% 0
1694|0);--sidebar-primary:oklch(48.8% .243 264.376);--sidebar-primary-foreground:oklch(98.5% 0
1695|0);--sidebar-accent:oklch(26.9% 0 0);--sidebar-accent-foreground:oklch(98.5% 0
1696|0);--sidebar-border:oklch(100% 0 0/.1);--sidebar-ring:oklch(55.6% 0
1697|0)}:root{--aura-font-family:-apple-system, BlinkMacSystemFont, "SF Pro Text", "SF Pro Display",
1698|"Helvetica Neue", sans-serif;--aura-font-display:-apple-system, BlinkMacSystemFont, "SF Pro
1699|Display", "SF Pro Text", "Helvetica Neue", sans-serif;--aura-font-mono:ui-monospace, "SF Mono",
1700|SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New",
1701|monospace;--aura-text-large-title-regular:400 26px/32px
1702|var(--aura-font-family);--aura-text-large-title-emphasized:700 26px/32px
1703|var(--aura-font-family);--aura-text-title-1-regular:400 22px/26px
1704|var(--aura-font-family);--aura-text-title-1-emphasized:700 22px/26px
1705|var(--aura-font-family);--aura-text-title-2-regular:400 17px/22px
1706|var(--aura-font-family);--aura-text-title-2-emphasized:700 17px/22px
1707|var(--aura-font-family);--aura-text-title-3-regular:400 15px/20px
1708|var(--aura-font-family);--aura-text-title-3-emphasized:590 15px/20px
1709|var(--aura-font-family);--aura-text-headline-regular:700 13px/16px
1710|var(--aura-font-family);--aura-text-headline-emphasized:860 13px/16px
1711|var(--aura-font-family);--aura-text-body-regular:400 13px/16px
1712|var(--aura-font-family);--aura-text-body-emphasized:590 13px/16px
1713|var(--aura-font-family);--aura-text-callout-regular:400 12px/15px
1714|var(--aura-font-family);--aura-text-callout-emphasized:590 12px/15px
1715|var(--aura-font-family);--aura-text-subheadline-regular:400 11px/14px
1716|var(--aura-font-family);--aura-text-subheadline-emphasized:590 11px/14px
1717|var(--aura-font-family);--aura-text-footnote-regular:400 10px/13px
1718|var(--aura-font-family);--aura-text-footnote-emphasized:590 10px/13px
1719|var(--aura-font-family);--aura-text-caption-1-regular:400 10px/13px
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