Summarization
Transformers
PyTorch
TensorBoard
Safetensors
English
t5
text2text-generation
Generated from Trainer
Eval Results (legacy)
text-generation-inference
Instructions to use sudoLife/tst-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sudoLife/tst-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="sudoLife/tst-summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sudoLife/tst-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("sudoLife/tst-summarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 528d4c456386698c82d5a9d3a17e2a3d5546348c75118ad0aedf0ac26d133e42
- Size of remote file:
- 242 MB
- SHA256:
- 6a800645f10361822ac890923d3c6aa9caac34493935a7efa925e6faa1a85a85
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