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
Download assets/mapo_tofu.mp4 from Tevatron/OmniEmbed-v0.1: direct link, hf CLI and curl.
- Browser
- Download file 5.25 MB
-
https://huggingface.co/Tevatron/OmniEmbed-v0.1/resolve/main/assets/mapo_tofu.mp4
- Command line
-
hf download hf://Tevatron/OmniEmbed-v0.1/assets/mapo_tofu.mp4
-
curl -L -o mapo_tofu.mp4 https://huggingface.co/Tevatron/OmniEmbed-v0.1/resolve/main/assets/mapo_tofu.mp4
5.25 MB
- Xet hash:
- 8e243ff37f9161b02830fd25d42fe35693050a181401bbb1c20845c0da00f841
- Size of remote file:
- 5.25 MB
- SHA256:
- 23bd7a2a9a554bc09084cb74e584ca6129292073efcd2350f180e81975f96ec5
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