Bonsai-27B-GGUF
lmstudio-community · Kit
A GGUF conversion of the 27B Bonsai model for LM Studio, with a 3.80 GB Q1_0 language file and a 0.93 GB BF16 vision projector. Tested for text, vision and par…
Lets you inspect how a Parquet file is built inside, from row groups and column chunks to pages, indexes, bloom filters and the footer. Runs in the browser, for data and ML engineers.
Parquet X-ray is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page, a zip of its files. Nothing in it runs by itself.
pip install -U huggingface_hub hf download cfahlgren1/parquet-xray --repo-type space --local-dir parquet-xray cd parquet-xray
Parquet X-ray is a browser tool for looking inside a Parquet file. It draws how the file is stored: the row groups, their column chunks and pages, plus the indexes, the bloom filters and the footer. You can open a page's details in a popover to see how the bytes are organized.
It suits people who work with Parquet files and want to see why a file is shaped the way it is, or learn the format.
| Industry | Who uses it | How they use it | Example |
|---|---|---|---|
| Data engineering | Data engineers | Check how row groups and pages are laid out in a file | An engineer opens a file to see how its columns are chunked |
| Machine learning | ML engineers | Inspect a dataset file from the Hub before loading it | An engineer looks at the footer of a Hub dataset file |
| Analytics | Analysts | Find out what indexes and bloom filters a file carries | An analyst checks whether a file has page indexes |
| Education | Students | Learn the Parquet format by looking at a real file | A student opens a file and follows it from footer to page |
You can skip it if you only read Parquet data through a library and never need the file's layout.
You use it in these places.
| Use case | Who | What they get back |
|---|---|---|
| Inspect a remote file | Data and ML engineers | The file's layout, read from a URL without downloading all of it |
| Inspect a local file | Anyone | The same layout view for a file you open from disk |
| Study the format | Students | A visual tour of row groups, column chunks and pages |
Online use needs only a browser. A local copy needs Python for the download step. Changing the code needs npm.
pip install -U huggingface_hub hf download cfahlgren1/parquet-xray --repo-type space --local-dir parquet-xray cd parquet-xray
To work on the code, the README gives these development commands.
npm install npm run dev npm run verify
Give the page the location of a Parquet file. That can be an address on the Hub, an hf:// path, a web address that permits CORS range requests, or a file you pick from your disk. The page reads only the footer and the page indexes, so a 2 GB file needs about 3 MB downloaded before it opens.
| Tool | What it does |
|---|---|
| npm install | Installs the project's dependencies |
| npm run dev | Starts the development server |
| npm run verify | Runs the lint, the type check, the tests and the build |
You paste the address of a Parquet file on the Hub. The page reads its footer and indexes, then shows the row groups. You open one to see its column chunks and pages, and click a page to see its details in a popover.
A Parquet file stores a table in blocks called row groups, and each column inside a block is a chunk made of pages. This page draws that structure. Try it by pasting the address of a file you know and opening the first row group.
Under the hood, the page uses range requests to read just the footer and page indexes, which is why a large file opens fast. Parsing uses the hyparquet library. The repository's config files point to Svelte, Vite and Playwright, and CONTRIBUTING.md explains how the code is organized.
Remote files must allow the kind of requests the page makes.
Lets you inspect how a Parquet file is built inside, from row groups and column chunks to pages, indexes, bloom filters and the footer. Runs in the browser, for data and ML engineers.
Made by cfahlgren1 on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face.
What it is: Parquet X-ray is a browser tool for looking inside a Parquet file. It draws how the file is stored: the row groups, their column chunks and pages, plus the indexes, the bloom filters and the footer. You can open a page's details in a popover to see how the bytes are organized.
Who it suits: It suits people who work with Parquet files and want to see why a file is shaped the way it is, or learn the format.
Industry | Who uses it | How they use it | Example
Data engineering | Data engineers | Check how row groups and pages are laid out in a file | An engineer opens a file to see how its columns are chunked
Machine learning | ML engineers | Inspect a dataset file from the Hub before loading it | An engineer looks at the footer of a Hub dataset file
Analytics | Analysts | Find out what indexes and bloom filters a file carries | An analyst checks whether a file has page indexes
Education | Students | Learn the Parquet format by looking at a real file | A student opens a file and follows it from footer to page
You can skip it if you only read Parquet data through a library and never need the file's layout.
Where to use it: You use it in these places.
Use case | Who | What they get back
Inspect a remote file | Data and ML engineers | The file's layout, read from a URL without downloading all of it
Inspect a local file | Anyone | The same layout view for a file you open from disk
Study the format | Students | A visual tour of row groups, column chunks and pages
How to set it up: Online use needs only a browser. A local copy needs Python for the download step. Changing the code needs npm.
pip install -U huggingface_hub
hf download cfahlgren1/parquet-xray --repo-type space --local-dir parquet-xray
cd parquet-xray
To work on the code, the README gives these development commands.
npm install
npm run dev
npm run verify
How to use it: Give the page the location of a Parquet file. That can be an address on the Hub, an hf:// path, a web address that permits CORS range requests, or a file you pick from your disk. The page reads only the footer and the page indexes, so a 2 GB file needs about 3 MB downloaded before it opens.
Tool | What it does
npm install | Installs the project's dependencies
npm run dev | Starts the development server
npm run verify | Runs the lint, the type check, the tests and the build
Example: You paste the address of a Parquet file on the Hub. The page reads its footer and indexes, then shows the row groups. You open one to see its column chunks and pages, and click a page to see its details in a popover.
For newcomers and experts: A Parquet file stores a table in blocks called row groups, and each column inside a block is a chunk made of pages. This page draws that structure. Try it by pasting the address of a file you know and opening the first row group.
Under the hood, the page uses range requests to read just the footer and page indexes, which is why a large file opens fast. Parsing uses the hyparquet library. The repository's config files point to Svelte, Vite and Playwright, and CONTRIBUTING.md explains how the code is organized.
Paste a URL or open a local file
Only the footer and page indexes are read
hyparquet parses the file's layout
Row groups, column chunks and pages are shown
Good to know: Remote files must allow the kind of requests the page makes.
Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself.
README.md 5 KB
Listed Hugging Face Spaces in the same category that share the most tags with this one.
| Product | Likes | Built with | License | Last change |
|---|---|---|---|---|
| Parquet X-ray This page | 7 | static | apache-2.0 | |
| InferenceSupportShares static | 764 | static | afl-3.0 | |
| HuggyShares static | 463 | static | cc-by-nc-sa-4.0 | |
| Z-Image Lookalike LoRA IndexShares static | 189 | static | apache-2.0 | |
| Granite Docling 258M WebGPUShares static | 163 | static | apache-2.0 | |
| DINOv3 WebShares static | 162 | static | apache-2.0 |
Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search and on Trendshift. Mindket doesn’t write or check them. Open one to read it where it was posted.
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