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README.md
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@@ -18,8 +18,9 @@ Run state-of-the-art ML workflows with a single command. From OCR to classificat
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UV scripts are self-contained Python scripts that use [inline metadata](https://docs.astral.sh/uv/guides/scripts/) to specify dependencies. Just `uv run script.py` and everything installs automatically.
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Perfect for:
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- π **Reproducible pipelines** that work anywhere
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## π Quick Example
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## π Browse Scripts
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| Script Collection
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| [ocr](https://huggingface.co/datasets/uv-scripts/ocr)
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| [classification](https://huggingface.co/datasets/uv-scripts/classification)
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| [dataset-creation](https://huggingface.co/datasets/uv-scripts/dataset-creation) | Create datasets from PDFs and files
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| [vllm](https://huggingface.co/datasets/uv-scripts/vllm)
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## π― Why UV Scripts?
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### Zero Setup
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No virtual environments, no dependency conflicts, no installation steps. UV handles everything automatically when you run the script.
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These aren't demos - they're production-quality tools used by the community for real ML workflows.
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### GPU Optimized
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Seamlessly run on local GPUs or scale to cloud with HF Jobs. Same script, different compute.
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Browse scripts, contribute your own, and learn from the best practices of the ML community.
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## π Featured Scripts
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### OCR Any Document Dataset
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Extract text from images with state-of-the-art accuracy:
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```bash
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# Handles LaTeX, tables, forms, handwriting
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uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/nanonets-ocr.py \
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your-images extracted-text
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```
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### Classify with Guaranteed Valid Outputs
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Text classification that always returns valid labels:
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```bash
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# Uses vLLM's structured generation - no invalid outputs!
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uv run https://huggingface.co/datasets/uv-scripts/classification/raw/main/classify-dataset.py \
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## π Getting Started
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1. **Install UV** (one-time setup):
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```bash
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curl -LsSf https://astral.sh/uv/install.sh | sh
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```
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2. **Run any script**:
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```bash
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uv run https://huggingface.co/datasets/uv-scripts/[collection]/raw/main/[script].py
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```
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## π€ Contributing
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We welcome scripts that:
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- Solve real ML problems
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- Include clear documentation
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- Follow UV best practices
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## π Learn More
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- [UV Documentation](https://docs.astral.sh/uv/)
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- [HF Jobs Guide](https://huggingface.co/docs/
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- [Script Examples](https://github.com/astral-sh/uv/tree/main/scripts)
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---
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-
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UV scripts are self-contained Python scripts that use [inline metadata](https://docs.astral.sh/uv/guides/scripts/) to specify dependencies. Just `uv run script.py` and everything installs automatically.
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Perfect for:
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- π **GPU workflows** on [HF Jobs](https://huggingface.co/docs/huggingface_hub/guides/jobs)
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- π» **Local processing** on your machine
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- π **Reproducible pipelines** that work anywhere
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## π Quick Example
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## π Browse Scripts
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| Script Collection | Description | GPU Required |
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| ------------------------------------------------------------------------------- | --------------------------------------------------------- | ------------ |
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| [ocr](https://huggingface.co/datasets/uv-scripts/ocr) | Extract text from images with VLMs (LaTeX, tables, forms) | β
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| [classification](https://huggingface.co/datasets/uv-scripts/classification) | Text classification with guaranteed valid outputs | β
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| [dataset-creation](https://huggingface.co/datasets/uv-scripts/dataset-creation) | Create datasets from PDFs and files | β |
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| [vllm](https://huggingface.co/datasets/uv-scripts/vllm) | High-performance inference with vLLM | β
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## π― Why UV Scripts?
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### Zero Setup
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No virtual environments, no dependency conflicts, no installation steps. UV handles everything automatically when you run the script.
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### GPU Optimized
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Seamlessly run on local GPUs or scale to cloud with HF Jobs. Same script, different compute.
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## π Featured Scripts
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### OCR Any Document Dataset
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Extract text from images with state-of-the-art accuracy:
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+
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```bash
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# Handles LaTeX, tables, forms, handwriting
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uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/nanonets-ocr.py \
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your-images extracted-text
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```
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### Classify with Guaranteed Valid Outputs
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Text classification that always returns valid labels:
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```bash
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# Uses vLLM's structured generation - no invalid outputs!
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uv run https://huggingface.co/datasets/uv-scripts/classification/raw/main/classify-dataset.py \
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## π Getting Started
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1. **Install UV** (one-time setup):
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```bash
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curl -LsSf https://astral.sh/uv/install.sh | sh
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```
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2. **Run any script**:
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```bash
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uv run https://huggingface.co/datasets/uv-scripts/[collection]/raw/main/[script].py
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```
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## π€ Contributing
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We welcome scripts that:
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- Solve real ML problems
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- Include clear documentation
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- Follow UV best practices
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## π Learn More
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- [UV Documentation](https://docs.astral.sh/uv/)
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- [HF Jobs Guide](https://huggingface.co/docs/huggingface_hub/guides/jobs)
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- [Script Examples](https://github.com/astral-sh/uv/tree/main/scripts)
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---
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_UV Scripts is a community project showcasing the power of [UV](https://github.com/astral-sh/uv) for ML workflows._
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