Visual Question Answering
Transformers
Safetensors
internvl_chat
feature-extraction
custom_code
8-bit precision
bitsandbytes
Instructions to use failspy/InternVL-Chat-V1-5-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use failspy/InternVL-Chat-V1-5-8bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="failspy/InternVL-Chat-V1-5-8bit", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("failspy/InternVL-Chat-V1-5-8bit", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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pipeline_tag: visual-question-answering
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# Model Card for InternVL-Chat-V1.5
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<p align="center">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/64119264f0f81eb569e0d569/D60YzQBIzvoCvLRp2gZ0A.jpeg" alt="Image Description" width="300" height="300" />
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pipeline_tag: visual-question-answering
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[Includes fixes for MultiGPU](https://github.com/OpenGVLab/InternVL/issues/96)
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# Model Card for InternVL-Chat-V1.5
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<p align="center">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/64119264f0f81eb569e0d569/D60YzQBIzvoCvLRp2gZ0A.jpeg" alt="Image Description" width="300" height="300" />
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