Summarization
Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
Eval Results (legacy)
text-generation-inference
Instructions to use autoevaluate/summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autoevaluate/summarization 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="autoevaluate/summarization")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("autoevaluate/summarization") model = AutoModelForSeq2SeqLM.from_pretrained("autoevaluate/summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add evaluation results on xsum
Beep boop, I am a bot from Hugging Face's automatic evaluation service! Your model has been evaluated on the [xsum](https://huggingface.co/datasets/xsum) dataset. Accept this pull request to see the results displayed on the [Hub leaderboard](https://huggingface.co/spaces/autoevaluate/leaderboards?dataset=xsum). Evaluate your model on more datasets [here](https://huggingface.co/spaces/autoevaluate/autoevaluate?dataset=xsum).98b11ea -
update model card README.md
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End of training
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Training in progress, step 500
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initial commit
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