Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
Eval Results (legacy)
text-generation-inference
Instructions to use shed-e/scipaper-summary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shed-e/scipaper-summary with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("shed-e/scipaper-summary") model = AutoModelForSeq2SeqLM.from_pretrained("shed-e/scipaper-summary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from shed-e/scipaper-summary: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/shed-e/scipaper-summary/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://shed-e/scipaper-summary/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/shed-e/scipaper-summary/resolve/main/pytorch_model.bin
242 MB
- Xet hash:
- 24ef14f3eeeaaf34209d88ed00315fca1c2f35c2e6d338977662975e028f8ddc
- Size of remote file:
- 242 MB
- SHA256:
- c4fbcfceece7859dd154e72ade556556f31a043a0efbd0d219a13946f6e80507
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