Instructions to use TamVT0203/t5small_textsummarize with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TamVT0203/t5small_textsummarize with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TamVT0203/t5small_textsummarize", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from TamVT0203/t5small_textsummarize: direct link, hf CLI and curl.
- Browser
- Download file 96 Bytes
-
https://huggingface.co/TamVT0203/t5small_textsummarize/resolve/main/README.md
- Command line
-
hf download hf://TamVT0203/t5small_textsummarize/README.md
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curl -L -o README.md https://huggingface.co/TamVT0203/t5small_textsummarize/resolve/main/README.md
96 Bytes
metadata
datasets:
- EdinburghNLP/xsum
language:
- en
metrics:
- rouge
library_name: transformers