Instructions to use pszemraj/distill-pegasus-CompMath with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pszemraj/distill-pegasus-CompMath with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("pszemraj/distill-pegasus-CompMath") model = AutoModelForSeq2SeqLM.from_pretrained("pszemraj/distill-pegasus-CompMath", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spiece.model from pszemraj/distill-pegasus-CompMath: direct link, hf CLI and curl.
- Browser
- Download file 1.91 MB
-
https://huggingface.co/pszemraj/distill-pegasus-CompMath/resolve/main/spiece.model
- Command line
-
hf download hf://pszemraj/distill-pegasus-CompMath/spiece.model
-
curl -L -o spiece.model https://huggingface.co/pszemraj/distill-pegasus-CompMath/resolve/main/spiece.model
1.91 MB
- Xet hash:
- 55f21cd07c01dbc516881febaff1d66b356b697e9acc0bb1a60776223300d4a2
- Size of remote file:
- 1.91 MB
- SHA256:
- 0015189ef36359283fec8b93cf6d9ce51bca37eb1101defc68a53b394913b96c
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