Summarization
Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
Eval Results (legacy)
text-generation-inference
Instructions to use domenicrosati/t5-small-finetuned-contradiction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use domenicrosati/t5-small-finetuned-contradiction 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="domenicrosati/t5-small-finetuned-contradiction")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("domenicrosati/t5-small-finetuned-contradiction") model = AutoModelForMultimodalLM.from_pretrained("domenicrosati/t5-small-finetuned-contradiction") - Notebooks
- Google Colab
- Kaggle
t5-small-finetuned-contradiction / runs /Apr27_11-07-38_nxhmkp5p5e /events.out.tfevents.1651057747.nxhmkp5p5e.109.0
- Xet hash:
- cd2a6f8bedb4218af6876894f5432c407646ea48ecbb9d52d79364171667e066
- Size of remote file:
- 9.78 kB
- SHA256:
- 5f3e5f53864cde84579bfd6bba4fec08982043aa9af6ac464fae086914aa6d01
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