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
| { | |
| "artifacts": { | |
| "legacy_manifest": "reports/vinci_v0/export/cilow_embed_v0_export_manifest.json", | |
| "onnx_manifest": "reports/vinci_v0/export/onnx_export.json", | |
| "onnx_model": "reports/vinci_v0/export/onnx/model.onnx", | |
| "tei_manifest": "reports/vinci_v0/export/tei_serving.json", | |
| "vinci_manifest": "reports/vinci_v0/export/vinci_v0_export_manifest.json" | |
| }, | |
| "dry_run": true, | |
| "full_dim": 1024, | |
| "low_dim": 256, | |
| "model_family": "vinci", | |
| "model_id": "Cilow/Vinci", | |
| "pipeline": "Lattice", | |
| "private_user_data": false, | |
| "requires_fresh_index": true, | |
| "similarity": "cosine", | |
| "source_model_dir": "reports/vinci_v0/model", | |
| "target": "all", | |
| "targets": [ | |
| "onnx", | |
| "tei" | |
| ] | |
| } |