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@@ -19,11 +19,11 @@ The model only takes images as document-side inputs and produce vectors represen
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  # News
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- - 2024-07-14: We released huggingface demo! Try our [online demo](https://huggingface.co/spaces/bokesyo/minicpm-visual-embeeding-v0-demo)!
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- - 2024-07-14: We released a Gradio demo of `miniCPM-visual-embedding-v0`, take a look at [pipeline_gradio.py](https://huggingface.co/RhapsodyAI/minicpm-visual-embedding-v0/blob/main/pipeline_gradio.py). You can run `pipeline_gradio.py` to build a demo on your PC.
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- - 2024-07-13: We released a command-line based demo of `miniCPM-visual-embedding-v0` for users to retireve most relavant pages from a given PDF file (could be very long), take a look at [pipeline.py](https://huggingface.co/RhapsodyAI/minicpm-visual-embedding-v0/blob/main/pipeline.py).
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  - 2024-06-27: 🚀 We released our first visual embedding model checkpoint minicpm-visual-embedding-v0 on [huggingface](https://huggingface.co/RhapsodyAI/minicpm-visual-embedding-v0).
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  huggingface-cli download --resume-download RhapsodyAI/minicpm-visual-embedding-v0 --local-dir minicpm-visual-embedding-v0 --local-dir-use-symlinks False
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  ```
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  ```python
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  from transformers import AutoModel
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  from transformers import AutoTokenizer
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  # Todos
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- - Release huggingface space demo.
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  - Release the evaluation results.
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  # News
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+ - 2024-07-14: We released **huggingface demo**! Try our [online demo](https://huggingface.co/spaces/bokesyo/minicpm-visual-embeeding-v0-demo)!
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+ - 2024-07-14: We released a **Gradio demo** of `miniCPM-visual-embedding-v0`, take a look at [pipeline_gradio.py](https://huggingface.co/RhapsodyAI/minicpm-visual-embedding-v0/blob/main/pipeline_gradio.py). You can run `pipeline_gradio.py` to build a demo on your PC.
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+ - 2024-07-13: We released a **command-line based demo** of `miniCPM-visual-embedding-v0` for users to retireve most relavant pages from a given PDF file (could be very long), take a look at [pipeline.py](https://huggingface.co/RhapsodyAI/minicpm-visual-embedding-v0/blob/main/pipeline.py).
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  - 2024-06-27: 🚀 We released our first visual embedding model checkpoint minicpm-visual-embedding-v0 on [huggingface](https://huggingface.co/RhapsodyAI/minicpm-visual-embedding-v0).
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  huggingface-cli download --resume-download RhapsodyAI/minicpm-visual-embedding-v0 --local-dir minicpm-visual-embedding-v0 --local-dir-use-symlinks False
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  ```
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+ - To deploy a local demo, first check `pipeline_gradio.py`, change *model path* to your local path and change *device* to your device (for users with Nvidia card, use 'cuda', for users with apple silicon, use 'mps'). then launch the demo:
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+
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+ ```bash
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+ pip install gradio
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+ python pipeline_gradio.py
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+ ```
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+ - To run the model for research purpose, please refer the following code:
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  ```python
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  from transformers import AutoModel
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  from transformers import AutoTokenizer
 
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  # Todos
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+ - [x] Release huggingface space demo.
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  - Release the evaluation results.
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