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daiweichen
/
pal-b-large-opt-350m

Summarization
Transformers
PyTorch
English
facebook/opt
feature-extraction
custom_code
Model card Files Files and versions
xet
Community
1

Instructions to use daiweichen/pal-b-large-opt-350m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use daiweichen/pal-b-large-opt-350m with Transformers:

    # Use a pipeline as a high-level helper
    # Warning: Pipeline type "summarization" is no longer supported in transformers v5.
    # You must load the model directly (see below) or downgrade to v4.x with:
    # 'pip install "transformers<5.0.0'
    from transformers import pipeline
    
    pipe = pipeline("summarization", model="daiweichen/pal-b-large-opt-350m", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("daiweichen/pal-b-large-opt-350m", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
pal-b-large-opt-350m
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  • 1 contributor
History: 22 commits
daiweichen's picture
daiweichen
Update README.md
ba7904a verified about 1 year ago
  • .gitattributes
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    initial commit about 1 year ago
  • README.md
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  • config.json
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  • configuration_pal_b_rm.py
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  • connector.py
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  • custom_sfx.py
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  • itemLearner.py
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  • learner.py
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  • modeling_pal_b_rm.py
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  • projector.py
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  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    1.33 GB
    xet
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  • tensor_initializer.py
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  • tensor_merger.py
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  • userLearner.py
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