Model reference · open weights
SkillRouter-Reranker is an open-weight embedding model from pipizhao, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
SR-Rank-0.6B SR-Rank-0.6B is a fine-tuned cross-encoder reranker for skill routing. It is designed to score a small candidate set of retrieved skills against a task query and select the single most relevant skill for an LLM agent. Model Summary - Base model: Qwen/Qwen3-Reranker-0.6B - Architecture: causal-LM-style cross-encoder reranker - Input: query + candidate skill text, formatted into the Qwen reranker prompt template - Output: scalar relevance score computed as logit(yes) - logit(no) - Intended use: rerank top-K candidates from a first-stage retriever such as SR-Emb-0.6B This model should be used on a candidate list, not as a standalone retriever over an 80K-scale corpus. Intended Uses Use SR-Rank-0.6B after a first-stage retriever has already narrowed a large corpus to a candidate set, for example: 1. Retrieve top-20 skills with pipizhao/SkillRouter-Embedding-0.6B. 2. Score each candidate with pipizhao/SkillRouter-Reranker-0.6B. 3. Sort by yes - no score. 4. Take the top-1 or top-N skills for downstream planning or execution. This model is not intended for free-form generation, chat, or long-document retrieval without candidate pruning. How to Use Citation If you use this model, please cite the SkillRouter paper once the preprint is public.
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | pipizhao |
|---|---|
| Type | Embedding models |
| Parameters (lead) | 596M |
| Context | 40k tokens |
| Variants | 1 |
| Runs with | transformers |
| Based on | Qwen/Qwen3-Reranker-0.6B |
| Released | 2026-03-26 |
| Popularity | 8k downloads / month |
| Likes | 6 |
| Licence | Open weights |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| SkillRouter-Reranker-0.6B | 596M | BF16 | ~1.4 GB | ✓ | Weights ↗ |
Using it via the API
Once AxForge deploys skillrouter-reranker for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (skillrouter-reranker below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/embeddings \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"skillrouter-reranker","input":"text to embed"}'
Licence
Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗
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