Text Retrieval
Safetensors
sentence-transformers
English
PyLate
modernbert
ColBERT
sentence-similarity
feature-extraction
late-interaction
reasoning-retrieval
edge
loss:CachedContrastive
Instructions to use DataScience-UIBK/SmallReason-ColBERT-32M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use DataScience-UIBK/SmallReason-ColBERT-32M 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="DataScience-UIBK/SmallReason-ColBERT-32M") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
Download 2_Dense/config.json from DataScience-UIBK/SmallReason-ColBERT-32M: direct link, hf CLI and curl.
- Browser
- Download file 137 Bytes
-
https://huggingface.co/DataScience-UIBK/SmallReason-ColBERT-32M/resolve/main/2_Dense/config.json
- Command line
-
hf download hf://DataScience-UIBK/SmallReason-ColBERT-32M/2_Dense/config.json
-
curl -L -o config.json https://huggingface.co/DataScience-UIBK/SmallReason-ColBERT-32M/resolve/main/2_Dense/config.json
137 Bytes
| {"in_features": 768, "out_features": 768, "bias": false, "activation_function": "torch.nn.modules.linear.Identity", "use_residual": true} |