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# Image Describer (vit-gpt2) β Hugging Face Space
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This Space runs nlpconnect/vit-gpt2-image-captioning with an optional T5 rewriter.
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- CPU-friendly and returns model outputs uncensored (no filter implemented).
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- Optional prompt box to bias the paraphrase step.
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To run locally:
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1. Create a Python 3.8+ venv and install requirements: `pip install -r requirements.txt`
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2. Run: `python app.py`
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Notes:
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- For production/throughput on CPU, reduce max_length/num_beams or convert to ONNX + quantize.
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- This Space uses the public HF model weights; no HF tokens are required to run the demo.
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