Instructions to use 51la5/T5-summary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 51la5/T5-summary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="51la5/T5-summary")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("51la5/T5-summary") model = AutoModel.from_pretrained("51la5/T5-summary") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:114c67c7e76cbdc687a1a5a75287c0bb8c5628e5183409b1d6776a2e6a7afc11
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size 242041896
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