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
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.models.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Dense", | |
| "type": "pylate.models.Dense.Dense" | |
| } | |
| ] |