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")# 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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a42d1debc9b40e2fdd71848c7aea19c2f1149b0effbda9fabc9523d93bf66a5f
- Size of remote file:
- 1.42 GB
- SHA256:
- c1d58f12c002cc35636a80ccf4d129043934e9f38675040bbef945f007b739f5
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