Summarization
Transformers
PyTorch
TensorBoard
bart
text2text-generation
Generated from Trainer
Eval Results (legacy)
Instructions to use cs608/billsum-model-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cs608/billsum-model-2 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-model-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cs608/billsum-model-2") model = AutoModelForSeq2SeqLM.from_pretrained("cs608/billsum-model-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from cs608/billsum-model-2: direct link, hf CLI and curl.
- Browser
- Download file 3.77 kB
-
https://huggingface.co/cs608/billsum-model-2/resolve/main/training_args.bin
- Command line
-
hf download hf://cs608/billsum-model-2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/cs608/billsum-model-2/resolve/main/training_args.bin
3.77 kB
- Xet hash:
- 4f1ff7011f860f9eb598d15197cde13fe47becb29c8e9af9d2122e25d727ef98
- Size of remote file:
- 3.77 kB
- SHA256:
- bbf9e03f91dae4b7c34f139de144922952b6d6497a341d613798ab7c16811c1f
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