Instructions to use CaseLoop/rti-formatter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CaseLoop/rti-formatter with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("CaseLoop/rti-formatter") model = AutoModelForSeq2SeqLM.from_pretrained("CaseLoop/rti-formatter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from CaseLoop/rti-formatter: direct link, hf CLI and curl.
- Browser
- Download file 5.39 kB
-
https://huggingface.co/CaseLoop/rti-formatter/resolve/main/training_args.bin
- Command line
-
hf download hf://CaseLoop/rti-formatter/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CaseLoop/rti-formatter/resolve/main/training_args.bin
5.39 kB
- Xet hash:
- dc44d60c4e34b0eb3dcb07959c85d19fa22f4f3ee09df14b4814a71de0d738ad
- Size of remote file:
- 5.39 kB
- SHA256:
- fb52620e8c546a26e64e6605ccb897c9dde25d0f7eb504719736a41a5f893126
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