Instructions to use premsuresh/bart-finetuned-mathqa-prem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use premsuresh/bart-finetuned-mathqa-prem with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("premsuresh/bart-finetuned-mathqa-prem") model = AutoModelForSeq2SeqLM.from_pretrained("premsuresh/bart-finetuned-mathqa-prem", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from premsuresh/bart-finetuned-mathqa-prem: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/premsuresh/bart-finetuned-mathqa-prem/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://premsuresh/bart-finetuned-mathqa-prem/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/premsuresh/bart-finetuned-mathqa-prem/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- 7f2c1fc4f8aefa2737d344ad49d39b8ebd359ebe9ef04cdf080a9f925c90389b
- Size of remote file:
- 558 MB
- SHA256:
- 65aa14e43d6c834275c3133843d62f3a19c2d7ff604b8462af0dcea455bd7468
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