Instructions to use hagara/roberta-large-three-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hagara/roberta-large-three-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hagara/roberta-large-three-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hagara/roberta-large-three-classification") model = AutoModelForSequenceClassification.from_pretrained("hagara/roberta-large-three-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hagara/roberta-large-three-classification: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/hagara/roberta-large-three-classification/resolve/refs%2Fpr%2F2/training_args.bin
- Command line
-
hf download hf://hagara/roberta-large-three-classification@refs/pr/2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hagara/roberta-large-three-classification/resolve/refs%2Fpr%2F2/training_args.bin
4.09 kB
- Xet hash:
- 114f4e77ea6efb53ba7d554f1a5cd18161e57a8385cd642866febdcf1764254e
- Size of remote file:
- 4.09 kB
- SHA256:
- b84e596d44d5af12b72da717209b83430b4c578fad5e2852d29778d308742e12
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