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aalto-ml
/
BayesVLM-Base

Feature Extraction
Transformers
PyTorch
English
clip
vision-language
probabilistic
uncertainty
custom_code
Model card Files Files and versions
xet
Community
1

Instructions to use aalto-ml/BayesVLM-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use aalto-ml/BayesVLM-Base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="aalto-ml/BayesVLM-Base", trust_remote_code=True)
    # Load model directly
    from transformers import AutoProcessor, AutoModel
    
    processor = AutoProcessor.from_pretrained("aalto-ml/BayesVLM-Base", trust_remote_code=True)
    model = AutoModel.from_pretrained("aalto-ml/BayesVLM-Base", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
BayesVLM-Base
1.23 GB
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  • 1 contributor
History: 3 commits
antonbaumann's picture
antonbaumann
Update README.md
e5b4b96 verified 3 months ago
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  • .gitattributes
    1.52 kB
    initial commit 3 months ago
  • README.md
    2.8 kB
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  • config.json
    631 Bytes
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  • merges.txt
    525 kB
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  • modeling_bayesvlm_clip.py
    18.8 kB
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  • preprocessor_config.json
    818 Bytes
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  • pytorch_model.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    611 MB
    xet
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  • special_tokens_map.json
    588 Bytes
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  • tokenizer.json
    2.22 MB
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  • tokenizer_config.json
    743 Bytes
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  • vocab.json
    862 kB
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