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
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README.md
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## Examples
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## Quickstart
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## Examples
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Input Images:
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<div style="display: flex; justify-content: center; gap: 20px;">
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<img src="ex1.jpg" width="200"/>
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<img src="ex2.jpg" width="300"/>
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</div>
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Input Queries:
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```
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queries = ["Chuyện gì xảy ra với quốc lộ 5 TP Hải Phòng ?","Phí giao hàng bao nhiêu ?"]
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```
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Output Scores:
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tensor([[60.7500, 64.5000],
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[62.7500, 60.7500]])
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```
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## Quickstart
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