Sentence Similarity
Safetensors
sentence-transformers
English
PyLate
modernbert
ColBERT
feature-extraction
Generated from Trainer
dataset_size:808728
loss:Distillation
text-embeddings-inference
Instructions to use himankhanda/colbert-modernbert-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use himankhanda/colbert-modernbert-large 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="himankhanda/colbert-modernbert-large") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
Download training_state.json from himankhanda/colbert-modernbert-large: direct link, hf CLI and curl.
- Browser
- Download file 56 Bytes
-
https://huggingface.co/himankhanda/colbert-modernbert-large/resolve/main/training_state.json
- Command line
-
hf download hf://himankhanda/colbert-modernbert-large/training_state.json
-
curl -L -o training_state.json https://huggingface.co/himankhanda/colbert-modernbert-large/resolve/main/training_state.json
56 Bytes
| { | |
| "num_train_epochs": 1, | |
| "last_logged_step": 50500 | |
| } |