Instructions to use blanchefort/rubert-base-cased-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use blanchefort/rubert-base-cased-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="blanchefort/rubert-base-cased-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("blanchefort/rubert-base-cased-sentiment") model = AutoModelForSequenceClassification.from_pretrained("blanchefort/rubert-base-cased-sentiment") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20cddfe2d9f9c347fdba577cf26c087e1e1ca36d56528a3a55e83e48a2a583d6
- Size of remote file:
- 712 MB
- SHA256:
- 17c5e6f11e5672c158b12ed629edb94a2d5adfb0c0eacf55c21d250c7381dac1
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