Sentence Similarity
Safetensors
sentence-transformers
English
PyLate
bert
ColBERT
feature-extraction
Generated from Trainer
dataset_size:497901
loss:Contrastive
text-embeddings-inference
Instructions to use souvickdascmsa019/initial-colbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use souvickdascmsa019/initial-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="souvickdascmsa019/initial-colbert") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0690d87c7d35137a030da60868b1ace4c3decaf54c1a416c23c1a590fb8c1fd8
- Size of remote file:
- 5.56 kB
- SHA256:
- bc79f90fbd4e4af766b84ef25beec473aea593f8e5f76062a7a882750e66962b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.