Sentence Similarity
Safetensors
sentence-transformers
English
PyLate
modernbert
ColBERT
multi-vector
feature-extraction
text-embeddings-inference
🇪🇺 Region: EU
Instructions to use lightonai/LateOn-hpool-regularized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lightonai/LateOn-hpool-regularized 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="lightonai/LateOn-hpool-regularized") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
Download 3_Dense/config.json from lightonai/LateOn-hpool-regularized: direct link, hf CLI and curl.
- Browser
- Download file 160 Bytes
-
https://huggingface.co/lightonai/LateOn-hpool-regularized/resolve/main/3_Dense/config.json
- Command line
-
hf download hf://lightonai/LateOn-hpool-regularized/3_Dense/config.json
-
curl -L -o config.json https://huggingface.co/lightonai/LateOn-hpool-regularized/resolve/main/3_Dense/config.json
160 Bytes
| { | |
| "in_features": 768, | |
| "out_features": 128, | |
| "bias": false, | |
| "activation_function": "torch.nn.modules.linear.Identity", | |
| "use_residual": false | |
| } |