Instructions to use Tevatron/OmniEmbed-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Tevatron/OmniEmbed-v0.1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Tevatron/OmniEmbed-v0.1") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - PEFT
How to use Tevatron/OmniEmbed-v0.1 with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 32c9f0c7318c176bac6ed5b3ad9600c9649ed8ec15883e27126616a4e00b6300
- Size of remote file:
- 7.99 kB
- SHA256:
- 2aa1c5377a2bc6b466167c7c56647789858c6f821b8cec25d642aa9a5a8b7465
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