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
Update pipeline tag and add paper link
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by nielsr HF Staff - opened
README.md
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language:
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- en
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tags:
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- ColBERT
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- PyLate
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- reasoning-retrieval
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- edge
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- loss:CachedContrastive
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base_model: mixedbread-ai/mxbai-edge-colbert-v0-32m
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datasets:
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- reasonir/reasonir-data
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- hanhainebula/bge-reasoner-data
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pipeline_tag: sentence-similarity
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library_name: PyLate
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license: cc-by-nc-4.0
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---
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# SmallReason-ColBERT (32M)
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An ultra-small late-interaction retriever for **reasoning-intensive** retrieval.
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32M parameters, plus a **129-parameter query-side importance head**.
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Not soft-IDF. Across ~199K BRIGHT query tokens the gate–IDF Spearman correlation is
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**ρ = −0.02** — statistically detectable, practically zero. Per-split mean gate sits in
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0.43–0.47 with std ≈ 0.10: the head is a soft re-weighting, not a selector. A fixed
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gate on the same base reaches only 20.06, against 21.41 for the learned head.
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---
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Thanks to Antoine Chaffin (LightOn, Reason-ModernColBERT) for flagging the upstream
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`2_Dense/use_residual` config bug in `mxbai-edge-colbert-v0-32m` — the base weights were
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trained with a residual on that layer while the shipped config said otherwise. This
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model uses the patched config (`use_residual: true`).
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---
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base_model: mixedbread-ai/mxbai-edge-colbert-v0-32m
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datasets:
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- reasonir/reasonir-data
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- hanhainebula/bge-reasoner-data
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language:
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- en
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library_name: PyLate
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license: cc-by-nc-4.0
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pipeline_tag: text-retrieval
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tags:
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- ColBERT
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- PyLate
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- reasoning-retrieval
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- edge
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- loss:CachedContrastive
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---
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# SmallReason-ColBERT (32M)
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**Paper**: [SmallReason-ColBERT: An Ultra-Small Late-Interaction Retriever for Reasoning Intensive Retrieval](https://huggingface.co/papers/2609.29652)
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An ultra-small late-interaction retriever for **reasoning-intensive** retrieval.
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32M parameters, plus a **129-parameter query-side importance head**.
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Not soft-IDF. Across ~199K BRIGHT query tokens the gate–IDF Spearman correlation is
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**ρ = −0.02** — statistically detectable, practically zero. Per-split mean gate sits in
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0.43–0.47 with std ≈ 0.10: the head is a soft re-weighting, not a selector. A fixed
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IDF gate on the same base reaches only 20.06, against 21.41 for the learned head.
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---
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Thanks to Antoine Chaffin (LightOn, Reason-ModernColBERT) for flagging the upstream
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`2_Dense/use_residual` config bug in `mxbai-edge-colbert-v0-32m` — the base weights were
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trained with a residual on that layer while the shipped config said otherwise. This
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+
model uses the patched config (`use_residual: true`).
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