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:
- aa71ace6bcf9119c64fe0fd9a24de0be46cfce29b88c9b868b5120d0602ab422
- Size of remote file:
- 242 MB
- SHA256:
- e69c822460a697b6a18242b190823cc9c0860b5b8d78d5690c5719f99d3d95e0
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