Summarization
Transformers
PyTorch
bart
text2text-generation
Generated from Trainer
Eval Results (legacy)
Instructions to use cs608/billsum-full-data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cs608/billsum-full-data 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="cs608/billsum-full-data")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cs608/billsum-full-data") model = AutoModelForSeq2SeqLM.from_pretrained("cs608/billsum-full-data") - Notebooks
- Google Colab
- Kaggle
Training complete
Browse files- generation_config.json +12 -0
- pytorch_model.bin +1 -1
generation_config.json
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{
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"bos_token_id": 0,
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"decoder_start_token_id": 2,
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"early_stopping": true,
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"eos_token_id": 2,
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"forced_bos_token_id": 0,
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"forced_eos_token_id": 2,
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"no_repeat_ngram_size": 3,
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"num_beams": 4,
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"pad_token_id": 1,
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"transformers_version": "4.29.1"
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 557971229
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version https://git-lfs.github.com/spec/v1
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oid sha256:a661f3707424fdd797184d39f2f2ac948e666c3d736cfb8f096114996e941e1e
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size 557971229
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