| Name | face-miner JSON |
| Version |
1.0.1
JSON |
| download |
| home_page | None |
| Summary | Extractor for HuggingFace models |
| upload_time | 2025-10-28 08:27:54 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | MIT License
Copyright (c) 2025 FaceMiner
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE. |
| keywords |
extractor
huggingface
library
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Hugging Face Extractor
A web-based tool to extract metadata for models from the Hugging Face Hub.
## Features
* Extract information for a single model or all models.
* Fetches metadata, tags, datasets, CO2 emissions, commits, discussions, and file manifests.
* Multi-threaded extraction for performance.
* Download the extracted data as a ZIP file containing multiple CSVs.
* Ability to resume a full crawl if interrupted.
## Installation
```bash
pip install face-miner
flask --app hf_extractor run
```
## Usage
1. Run the Flask application.
2. Open your web browser and navigate to `http://127.0.0.1:5050`.
3. Use the web interface to start the extraction process.
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