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@@ -90,11 +90,23 @@ Install `gradio` first.
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  pip install gradio
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  ```
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- Adapt the code in `pipeline_gradio.py` according to your device.
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- - For M1/M2/M3 users, please make sure `model = model.to(device='mps', dtype=torch.float16)` then run `PYTORCH_ENABLE_MPS_FALLBACK=1 python pipeline_gradio.py`.
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- - For x86 CPU users, please remove `model = model.to(device)` then run `python pipeline_gradio.py`.
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- - For x86 CPU + Nvidia GPU users, please make sure `model = model.to('cuda')` then run `python pipeline_gradio.py`.
 
 
 
 
 
 
 
 
 
 
 
 
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  - If you encountered an error, please open an issue [here](https://huggingface.co/RhapsodyAI/minicpm-visual-embedding-v0/discussions), we will respond soon.
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  pip install gradio
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  ```
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+ Clone demo source code.
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+ - For retrieval-only demo (without generation), you should clone https://huggingface.co/spaces/bokesyo/MiniCPM_Visual_Document_Retriever_Demo.
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+ - For retrieval and generation (full RAG pipeline), you should clone https://huggingface.co/spaces/bokesyo/MiniCPMV-RAG-PDFQA.
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+
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+ ```bash
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+ git clone https://huggingface.co/spaces/bokesyo/MiniCPM_Visual_Document_Retriever_Demo
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+ git clone https://huggingface.co/spaces/bokesyo/MiniCPMV-RAG-PDFQA
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+ ```
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+
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+ For `retrieval and generation` demo, you need to also install `flash_attn`.
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+ Adapt the code in `app.py` according to your device.
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+
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+ - For M1/M2/M3 users, please make sure `model = model.to(device='mps', dtype=torch.float16)` then run `PYTORCH_ENABLE_MPS_FALLBACK=1 python app.py`.
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+ - For x86 CPU users, please remove `model = model.to(device)` then run `python app.py`.
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+ - For x86 CPU + Nvidia GPU users, please make sure `model = model.to('cuda')` then run `python app.py`.
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  - If you encountered an error, please open an issue [here](https://huggingface.co/RhapsodyAI/minicpm-visual-embedding-v0/discussions), we will respond soon.
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