Sentence Similarity
Safetensors
sentence-transformers
Italian
pylate
modernbert
colbert
late-interaction
italian
retrieval
information-retrieval
rag
multi-vector
text-embeddings-inference
Instructions to use enricollen/ItColBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use enricollen/ItColBERT with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("enricollen/ItColBERT") sentences = [ "Questa è una persona felice", "Questo è un cane felice", "Questa è una persona molto felice", "Oggi è una giornata di sole" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| { | |
| "in_features": 768, | |
| "out_features": 128, | |
| "bias": false, | |
| "activation_function": "torch.nn.modules.linear.Identity", | |
| "use_residual": false | |
| } |