Instructions to use OpenGVLab/VideoChat-TPO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/VideoChat-TPO with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenGVLab/VideoChat-TPO", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add paper link and library name
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by nielsr HF Staff - opened
README.md
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base_model:
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- mistralai/Mistral-7B-Instruct-v0.2
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license: mit
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pipeline_tag: video-text-to-text
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---
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# VideoChat2-TPO
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## 🏃 Installation
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```
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base_model:
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library_name: transformers
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license: mit
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pipeline_tag: video-text-to-text
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---
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# VideoChat2-TPO
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This model is based on the paper [Task Preference Optimization: Improving Multimodal Large Language Models with Vision Task Alignment](https://huggingface.co/papers/2412.19326).
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## 🏃 Installation
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```
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