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 training_args.bin from premsuresh/bart-finetuned-mathqa-decomposition: direct link, hf CLI and curl.
- Browser
- Download file 3.44 kB
-
https://huggingface.co/premsuresh/bart-finetuned-mathqa-decomposition/resolve/main/training_args.bin
- Command line
-
hf download hf://premsuresh/bart-finetuned-mathqa-decomposition/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/premsuresh/bart-finetuned-mathqa-decomposition/resolve/main/training_args.bin
3.44 kB
- Xet hash:
- aee3847be6be491b8a2facc5ac80366aaa163d92ee287458e58cf2841b950567
- Size of remote file:
- 3.44 kB
- SHA256:
- 1829fa9361148f288394fafa45d43116803cc9ba180a6dae2ca47a60f3349a50
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