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@@ -28,19 +28,10 @@ All the power of GPU‑accelerated OCR, yet you **only pay for GPU seconds you a
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## 🚀 Deploy your own
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2. Upload the three project files (`app.py`, `requirements.txt`, `README.md`) *or* just drop in the ZIP bundle.
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3. **Commit** – the Space builds automatically. The first OCR call downloads EasyOCR model weights (~200 MB per language group).
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## 💡 Usage tips
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* Large PDFs can take several minutes; the GPU reservation duration is `600 s`. Tweak the `@spaces.GPU(duration=…)` decorator if needed.
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* For faster queues, lower the duration or split very large documents.
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* When you know your PDF is **text only**, selecting **native** mode skips GPU altogether for near‑instant results.
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## 🏗️ Contributing
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* Code style: `black app.py` and `ruff app.py`.
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* Test: run `pytest tests/` (sample fixtures provided).
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Happy extracting! 📚
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## 🚀 Deploy your own
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**Note**: The first OCR call downloads EasyOCR model weights (~200 MB per language group).
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## 💡 Usage tips
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* Large PDFs can take several minutes; the GPU reservation duration is `600 s`. Tweak the `@spaces.GPU(duration=…)` decorator if needed.
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* For faster queues, lower the duration or split very large documents.
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* When you know your PDF is **text only**, selecting **native** mode skips GPU altogether for near‑instant results.
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