Summarization
Transformers
PyTorch
TensorBoard
mt5
text2text-generation
Generated from Trainer
Eval Results (legacy)
Instructions to use chrisjay/cos801-802-hf-workshop-mt5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chrisjay/cos801-802-hf-workshop-mt5-small 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="chrisjay/cos801-802-hf-workshop-mt5-small")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("chrisjay/cos801-802-hf-workshop-mt5-small") model = AutoModelForSeq2SeqLM.from_pretrained("chrisjay/cos801-802-hf-workshop-mt5-small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f51d36d246674e0cb7f53fcd4538d143bea7e4d83702bb04847d83cb2d2a8d4
- Size of remote file:
- 3.57 kB
- SHA256:
- 9cc0a0c85a288bc950ad7122da2ff93e2687833b94f603f187bf9be2aac272de
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