Instructions to use nandezgarcia/roberta-base-bne-finetuned-recores with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nandezgarcia/roberta-base-bne-finetuned-recores with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultipleChoice tokenizer = AutoTokenizer.from_pretrained("nandezgarcia/roberta-base-bne-finetuned-recores") model = AutoModelForMultipleChoice.from_pretrained("nandezgarcia/roberta-base-bne-finetuned-recores", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nandezgarcia/roberta-base-bne-finetuned-recores: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/nandezgarcia/roberta-base-bne-finetuned-recores/resolve/main/training_args.bin
- Command line
-
hf download hf://nandezgarcia/roberta-base-bne-finetuned-recores/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nandezgarcia/roberta-base-bne-finetuned-recores/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- 71cf5455596bab42d545f96c0a55b9f853c555301ed56d04579ad622ee7216a2
- Size of remote file:
- 3.06 kB
- SHA256:
- 3ae98400097687f5ffa062bc791d23bac2c1058b11d322a78ba95eb098dd5459
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