Instructions to use chihun-jang/mainCut-label9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chihun-jang/mainCut-label9 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="chihun-jang/mainCut-label9")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("chihun-jang/mainCut-label9") model = AutoModelForSequenceClassification.from_pretrained("chihun-jang/mainCut-label9", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from chihun-jang/mainCut-label9: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/chihun-jang/mainCut-label9/resolve/main/training_args.bin
- Command line
-
hf download hf://chihun-jang/mainCut-label9/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/chihun-jang/mainCut-label9/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- fe2db88c74413fd119b1b3c66a0366be6dbdc564afdf5979bafd0e7dda77fbfe
- Size of remote file:
- 4.03 kB
- SHA256:
- dc662baf166efa56b7a5ae96ab249fa63434350f82299e407be59b02b512454e
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