Instructions to use 5CD-AI/ColVintern-1B-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 5CD-AI/ColVintern-1B-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="5CD-AI/ColVintern-1B-v1", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("5CD-AI/ColVintern-1B-v1", trust_remote_code=True, dtype="auto") - ColPali
How to use 5CD-AI/ColVintern-1B-v1 with ColPali:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +1 -2
config.json
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@@ -6,8 +6,7 @@
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"auto_map": {
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"AutoConfig": "5CD-AI/ColVintern-1B-v1--configuration_internvl_chat.InternVLChatConfig",
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"AutoModel": "5CD-AI/ColVintern-1B-v1--modeling_colinternvl2.ColInternVL2",
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"AutoModelForCausalLM": "5CD-AI/ColVintern-1B-v1--modeling_colinternvl2.ColInternVL2"
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"AutoProcessor": "5CD-AI/ColVintern-1B-v1--processing_colinternvl2.ColInternVL2Processor",
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},
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"downsample_ratio": 0.5,
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"dynamic_image_size": true,
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"auto_map": {
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"AutoConfig": "5CD-AI/ColVintern-1B-v1--configuration_internvl_chat.InternVLChatConfig",
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"AutoModel": "5CD-AI/ColVintern-1B-v1--modeling_colinternvl2.ColInternVL2",
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"AutoModelForCausalLM": "5CD-AI/ColVintern-1B-v1--modeling_colinternvl2.ColInternVL2"
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},
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"downsample_ratio": 0.5,
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"dynamic_image_size": true,
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