Sentence Similarity
Safetensors
sentence-transformers
PyLate
modernbert
ColBERT
feature-extraction
Generated from Trainer
dataset_size:640000
loss:Distillation
Eval Results (legacy)
text-embeddings-inference
Instructions to use patrick-358/my-gte-colbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use patrick-358/my-gte-colbert with sentence-transformers:
from pylate import models queries = [ "Which planet is known as the Red Planet?", "What is the largest planet in our solar system?", ] documents = [ ["Mars is the Red Planet.", "Venus is Earth's twin."], ["Jupiter is the largest planet.", "Saturn has rings."], ] model = models.ColBERT(model_name_or_path="patrick-358/my-gte-colbert") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
| [ | |
| { "idx": 0, "name": "0", "path": "", "type": "sentence_transformers.models.Transformer" }, | |
| { "idx": 1, "name": "1", "path": "1_Pooling", "type": "sentence_transformers.models.Pooling" }, | |
| { "idx": 2, "name": "2", "path": "1_Dense", "type": "sentence_transformers.models.Dense" } | |
| ] |