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sjrhuschlee
/
flan-t5-base-squad2

Question Answering
Transformers
PyTorch
Safetensors
English
t5
squad
squad_v2
custom_code
Eval Results (legacy)
text-generation-inference
Model card Files Files and versions
xet
Community
1

Instructions to use sjrhuschlee/flan-t5-base-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use sjrhuschlee/flan-t5-base-squad2 with Transformers:

    # Use a pipeline as a high-level helper
    # Warning: Pipeline type "question-answering" 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("question-answering", model="sjrhuschlee/flan-t5-base-squad2", trust_remote_code=True)
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForQuestionAnswering
    
    tokenizer = AutoTokenizer.from_pretrained("sjrhuschlee/flan-t5-base-squad2", trust_remote_code=True)
    model = AutoModelForQuestionAnswering.from_pretrained("sjrhuschlee/flan-t5-base-squad2", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
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Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

TemporalMesh Transformer: 29.4 PPL at 48% compute — beats Mamba, new open-source architecture

#1 opened 5 months ago by
vigneshwar234
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