Instructions to use DeepPavlov/rubert-base-cased-conversational with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepPavlov/rubert-base-cased-conversational with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="DeepPavlov/rubert-base-cased-conversational")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("DeepPavlov/rubert-base-cased-conversational") model = AutoModel.from_pretrained("DeepPavlov/rubert-base-cased-conversational") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 633d8dadcb14b79b1433f00d31d7dad7f7390468d74752f49826c2987cb68096
- Size of remote file:
- 714 MB
- SHA256:
- a299b6726dbe7d7e082124e1260d1c7c94e8a2a3552712f66c141b25d4ba2fac
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