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 pytorch_model.bin from CoReProg/7class_PR: direct link, hf CLI and curl.
- Browser
- Download file 557 MB
-
https://huggingface.co/CoReProg/7class_PR/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://CoReProg/7class_PR@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/CoReProg/7class_PR/resolve/refs%2Fpr%2F1/pytorch_model.bin
557 MB
- Xet hash:
- d302eda6da1bf4116662172e3ad08ac4c9c0cf09940f87a5516812221729492d
- Size of remote file:
- 557 MB
- SHA256:
- 886a6633766bfe95a35042fb809e34ba2356dcf1e2f00ced73ebaaca612ef656
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