Feature Extraction
sentence-transformers
Safetensors
English
text-embeddings-inference
embeddings
retrieval
matryoshka
lattice
cilow
db-native
claim-aware
Instructions to use GeneralizedLabs/Vinci with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use GeneralizedLabs/Vinci with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("GeneralizedLabs/Vinci") 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] - Notebooks
- Google Colab
- Kaggle
| { | |
| "base_model": "BAAI/bge-m3", | |
| "dataset_repo": "Cilow/Vinci-Evals", | |
| "full_dim": 1024, | |
| "generated_at": "2026-05-02T02:51:25+00:00", | |
| "legacy_model_ids": [ | |
| "cilow/vinci-v0", | |
| "cilow/cilow-embed-v0" | |
| ], | |
| "low_dim": 256, | |
| "model_family": "vinci", | |
| "model_id": "Cilow/Vinci", | |
| "pipeline": "Lattice", | |
| "private_user_data": false, | |
| "requires_fresh_index": true, | |
| "semantic_space_must_match_model_id": true, | |
| "serializer_version": "claim_v1", | |
| "similarity": "cosine" | |
| } | |