Instructions to use certainstar/Trained-Mul-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use certainstar/Trained-Mul-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="certainstar/Trained-Mul-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("certainstar/Trained-Mul-classification") model = AutoModelForSequenceClassification.from_pretrained("certainstar/Trained-Mul-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from certainstar/Trained-Mul-classification: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/certainstar/Trained-Mul-classification/resolve/main/training_args.bin
- Command line
-
hf download hf://certainstar/Trained-Mul-classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/certainstar/Trained-Mul-classification/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- 9593a7dca7f7db27f3908374d778b9ae2b08146fc8e79b1ded3d868b10935618
- Size of remote file:
- 5.05 kB
- SHA256:
- dfc7e249f4a7941cc06989f6ec1445b35f11da2753e6b814d6ce30cd3a2190a7
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