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
- Xet hash:
- b9afe7bda19727998a29f55f0595790214cb9ac9637c69a4e5d7a800e69aaf6d
- Size of remote file:
- 11.4 MB
- SHA256:
- 63a3df087afa0c8890b416fe2c4f3f2593f06181adda4aacf93db8eb34cf0208
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