Instructions to use CoReProg/7class_PR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CoReProg/7class_PR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CoReProg/7class_PR")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CoReProg/7class_PR") model = AutoModelForSequenceClassification.from_pretrained("CoReProg/7class_PR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from CoReProg/7class_PR: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/CoReProg/7class_PR/resolve/main/training_args.bin
- Command line
-
hf download hf://CoReProg/7class_PR/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CoReProg/7class_PR/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- ff9280b1518a147e46379eed21d1b4c287b80380daf6dd0c91f7b25a681bfa67
- Size of remote file:
- 3.38 kB
- SHA256:
- 79d0594ac8ef40ae907bba47823d560a7397fac19c14f1d9344ac0d2a34f1f08
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