Instructions to use MonoHime/rubert_conversational_cased_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MonoHime/rubert_conversational_cased_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MonoHime/rubert_conversational_cased_sentiment")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MonoHime/rubert_conversational_cased_sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 07406b30c265ff2a4e5e66a296268420f637f2336648decf8fa525df7873de40
- Size of remote file:
- 714 MB
- SHA256:
- fc968f65e8a0e481033c2f1dced07d29da62365161e4eb7f6f4e755d74d9c260
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