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tencent/R3-rerank-0.6b
R3-rerank-0.6b is a text ranking model from tencent. Use it for the text ranking task on the model card, and read the license before you ship it in a product. It is set up for sentence-transformers. The card lists the license as apache-2.0.
The latest agent skill reranking model at the 0.6B scale. R3-Reranker is the cross-encoder (rerank) stage of R3-Skill's two-stage retriever for query-conditional agent skill retrieval. It scores each (query, skill) pa…
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From the Hugging Face model README
The latest agent skill reranking model at the 0.6B scale. R3-Reranker is the cross-encoder (rerank) stage of R3-Skill's two-stage retriever for query-conditional agent skill retrieval. It scores each (query, skill) pair jointly, paired with R3-Embedding-0.6B for recall.
from sentence_transformers import CrossEncoder
model = CrossEncoder("tencent/R3-rerank-0.6b")
query = "I need to compose music"
skills = [ # The format is "name | description | skill_md"
"music-composer | Composes original music | Creates music for various media formats ...",
"music-lyricist | Writes lyrics for songs | Creates lyrics for various music genres ...",
"music-editor | Edits and mixes music tracks | Provides audio editing and mixing services ...",
]
pairs = [(query, skill) for skill in skills]
scores = model.predict(pairs)
print(scores)
# [ 0.34937477 -1.7738094 -1.6604462 ]
@inproceedings{r3skill2026,
title = {Skill Is Not Document: A Query-Conditional Benchmark and Two-Stage Retriever for LLM Agent Skill Routing},
author = {Wang, Zifei and Wen, Wei and Ji, Qiang and Qiao, Ruizhi and Sun, Xing},
year = {2026},
url = {https://arxiv.org/abs/2606.03565},
}