Instructions to use premsuresh/bart-finetuned-mathqa-decomposition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use premsuresh/bart-finetuned-mathqa-decomposition with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("premsuresh/bart-finetuned-mathqa-decomposition") model = AutoModelForSeq2SeqLM.from_pretrained("premsuresh/bart-finetuned-mathqa-decomposition", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from premsuresh/bart-finetuned-mathqa-decomposition: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/premsuresh/bart-finetuned-mathqa-decomposition/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://premsuresh/bart-finetuned-mathqa-decomposition/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/premsuresh/bart-finetuned-mathqa-decomposition/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- 60f713e2b312ae582509f8749d4bd63783dcbd67c2692e0a06168011b8065c31
- Size of remote file:
- 558 MB
- SHA256:
- dbeff097700ea245aa14170b33fd2f3645a3e4f71b770fe9d66c8bfde230bdad
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