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 training_args.bin from premsuresh/bart-finetuned-mathqa: direct link, hf CLI and curl.
- Browser
- Download file 3.44 kB
-
https://huggingface.co/premsuresh/bart-finetuned-mathqa/resolve/main/training_args.bin
- Command line
-
hf download hf://premsuresh/bart-finetuned-mathqa/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/premsuresh/bart-finetuned-mathqa/resolve/main/training_args.bin
3.44 kB
- Xet hash:
- c98cd9d6c446f9be4cfe35b78e478a154dbb1c09509ad06b3bcd204c5941d22a
- Size of remote file:
- 3.44 kB
- SHA256:
- c48a2293ae6f5421c8ed4a2c41a2f1f9cf7b8f03208b05cf48aa480c30d098d6
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