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
File size: 97 Bytes
fa8be31 | 1 2 3 4 5 6 | {
"embedding_dimension": 3584,
"pooling_mode": "lasttoken",
"include_prompt": true
}
|