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:
- f59fce72f616172554e519584834dd7b49bdc28f94a018b533f17d49de8d78d1
- Size of remote file:
- 11.4 MB
- SHA256:
- 8441917e39ae0244e06d704b95b3124795cec478e297f9afac39ba670d7e9d99
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