Summarization
Transformers
TensorBoard
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use paulh27/xsum_unaligned_smallT5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use paulh27/xsum_unaligned_smallT5 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="paulh27/xsum_unaligned_smallT5")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("paulh27/xsum_unaligned_smallT5") model = AutoModelForSeq2SeqLM.from_pretrained("paulh27/xsum_unaligned_smallT5") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- Apr15_15-27-43_nlpg03.cs.washington.edu
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- Apr15_16-41-31_nlpg03.cs.washington.edu
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- Apr15_17-08-31_nlpg03.cs.washington.edu
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- Apr15_17-21-55_nlpg03.cs.washington.edu
- Apr15_17-22-26_nlpg03.cs.washington.edu
- Apr15_17-23-17_nlpg03.cs.washington.edu