Instructions to use premsuresh/bart-finetuned-mathqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use premsuresh/bart-finetuned-mathqa with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("premsuresh/bart-finetuned-mathqa") model = AutoModelForSeq2SeqLM.from_pretrained("premsuresh/bart-finetuned-mathqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from premsuresh/bart-finetuned-mathqa: direct link, hf CLI and curl.
- Browser
- Download file 1.63 GB
-
https://huggingface.co/premsuresh/bart-finetuned-mathqa/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://premsuresh/bart-finetuned-mathqa/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/premsuresh/bart-finetuned-mathqa/resolve/main/pytorch_model.bin
1.63 GB
- Xet hash:
- 6b5582a1df1fc8868ef2712fb4da4fe454385b884d57fb28f57072d16543a7fd
- Size of remote file:
- 1.63 GB
- SHA256:
- eaf463f92c5dcb7137987669f2e7676a6c2d7be21e367dc3f6dee474ac1ce877
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