Instructions to use radna/mini_intern_chat_triton with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use radna/mini_intern_chat_triton with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="radna/mini_intern_chat_triton", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("radna/mini_intern_chat_triton", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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> _Two interns holding hands, symbolizing the integration of InternViT and InternLM._
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You can run multimodal large models using a 1080Ti now.
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## Performance
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 [\[📜 InternVL 1.0 Paper\]](https://arxiv.org/abs/2312.14238) [\[📜 InternVL 1.5 Report\]](https://arxiv.org/abs/2404.16821) [\[🗨️ Chat Demo\]](https://internvl.opengvlab.com/) [\[🤗 HuggingFace Demo\]](https://huggingface.co/spaces/OpenGVLab/InternVL)
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[\[🚀 Quick Start\]](#model-usage) [\[🌐 Community-hosted API\]](https://rapidapi.com/adushar1320/api/internvl-chat) [\[📖 中文解读\]](https://zhuanlan.zhihu.com/p/675877376)
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You can run multimodal large models using a 1080Ti now.
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## Performance
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## Model Usage
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