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
Add TF weights
#1
by joaogante - opened
- tf_model.h5 +3 -0
tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:96f914cb927f82ea8bb53d1ac06c99d3660831b5b9ba84b74d03e17d1e64fc62
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size 711681000
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