Instructions to use paulh27/xsum_aligned_smallT5_cont3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use paulh27/xsum_aligned_smallT5_cont3 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("paulh27/xsum_aligned_smallT5_cont3") model = AutoModelForSeq2SeqLM.from_pretrained("paulh27/xsum_aligned_smallT5_cont3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from paulh27/xsum_aligned_smallT5_cont3: direct link, hf CLI and curl.
- Browser
- Download file 2.42 MB
-
https://huggingface.co/paulh27/xsum_aligned_smallT5_cont3/resolve/c60544fcbf2cd868014da28481baab5cf3ee1713/tokenizer.json
- Command line
-
hf download hf://paulh27/xsum_aligned_smallT5_cont3@c60544fcbf2cd868014da28481baab5cf3ee1713/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/paulh27/xsum_aligned_smallT5_cont3/resolve/c60544fcbf2cd868014da28481baab5cf3ee1713/tokenizer.json
2.42 MB
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