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
| { | |
| "baseline_model_id": "BAAI/bge-m3", | |
| "claim_policy": "2x means >=2.0 error reduction, where error = 1 - metric", | |
| "eligible_for_2x_claim": false, | |
| "metric": "ndcg_at_10", | |
| "model_family": "vinci", | |
| "model_id": "Cilow/Vinci", | |
| "pipeline": "Lattice", | |
| "rows": [ | |
| { | |
| "baseline": 0.77, | |
| "baseline_error": 0.22999999999999998, | |
| "candidate": 0.76, | |
| "candidate_error": 0.24, | |
| "error_reduction": 0.9583333333333333, | |
| "metric": "ndcg_at_10", | |
| "model_id": "Cilow/Vinci", | |
| "task": "FiQA2018", | |
| "track": "embedding", | |
| "two_x": false | |
| }, | |
| { | |
| "baseline": 0.67, | |
| "baseline_error": 0.32999999999999996, | |
| "candidate": 0.66, | |
| "candidate_error": 0.33999999999999997, | |
| "error_reduction": 0.9705882352941176, | |
| "metric": "ndcg_at_10", | |
| "model_id": "Cilow/Vinci", | |
| "task": "NFCorpus", | |
| "track": "embedding", | |
| "two_x": false | |
| }, | |
| { | |
| "baseline": 0.72, | |
| "baseline_error": 0.28, | |
| "candidate": 0.71, | |
| "candidate_error": 0.29000000000000004, | |
| "error_reduction": 0.9655172413793103, | |
| "metric": "ndcg_at_10", | |
| "model_id": "Cilow/Vinci", | |
| "task": "SciFact", | |
| "track": "embedding", | |
| "two_x": false | |
| } | |
| ] | |
| } |