Qwen3-4B ReST Fused — model card
base_model: Qwen/Qwen3-4B-Instruct-2507
language:
- en
library_name: mlx
license: other
pipeline_tag: text-generation
tags:
- posttrainllm
- mlx
- tool-calling
- function-calling
- agentic
- rest
- research-specialist
Qwen3-4B ReST Fused
Model description
A research specialist built by PostTrainLLM — a Mac-local LLM factory that post-trains small models for narrow agentic tasks. This model preserves the best measured Qwen3-4B agentic candidate produced by a teacher-free ReST (Reinforced Self-Training) loop. One ReST iteration recovered the out-of-domain breadth lost by narrow distillation while retaining the saturated file-operations gate.
It is a research specialist package, not the default Pace planner. The model speaks BFCL/OpenAI-style tool calls; Pace uses a different intent envelope and requires its own ship gate.
- Base model:
Qwen/Qwen3-4B-Instruct-2507 - Precision: bf16
- Format: fused HF/MLX safetensors directory (8 files, ~8 GB)
- Architecture: Qwen3ForCausalLM
- Compatibility:
mlx_lm,posttrainllm serve --hf-dir
Eval results
The current numbers come from the fresh paired run on 2026-09-03. Source:
qwen3-4b-rest-fused.json.
| Suite | Stock 4B | ReST 4B | Delta | n |
|---|---|---|---|---|
| File-ops hard gate | 0.75 | 1.00 | +0.25 | 12 |
| Qualified breadth | 0.667 | 0.556 | -0.111 | 45 |
The breadth ruler passed its frontier gate at 44/45. ReST reached 12/12 on file-ops, removed all eight stock side effects, and ran that slice 2.42x faster wall-clock. It also lost five net breadth cases versus stock. This confirms a routed file-ops win and rejects the candidate as a general successor.
Evidence quality caveat: raw traces remain local and gitignored, with their
SHA-256 receipts preserved in
evals/verified-wins/rest-requalification-result-v1.json. The legacy package
report-card adapter cannot promote those run fields to a fully verified ship.
Training recipe summary
- Target: same GorillaFileSystem file-ops depth anchor as the distilled specialist, plus breadth recovery across TradingBot, VehicleControlAPI, and TravelAPI backends.
- Method: teacher-free ReST — one iteration over checker-passing interleaved trajectories. No paid model API was used (training cost: $0). The checker validated tool-call correctness; passing trajectories were folded back into the training set.
- Depth anchor: file-ops gold depth was preserved as an anchor so ReST could not regress the saturated 100% hard gate while recovering breadth.
- Student: Qwen3-4B-Instruct-2507 bf16, fused into a single HF/MLX safetensors directory.
- Decision: retain only as a routed file-ops specialist; reject as a general successor and do not use as the Pace default planner.
Limitations
- Breadth regression. The frontier-qualified candidate scored 25/45 versus stock 30/45. Do not market it as breadth recovery or a general replacement.
- Raw predictions are not committed. Their hashes are preserved in the tracked result, but the files remain local and gitignored.
- Training duration and normalized latency remain absent. Fresh eval wall time, tok/s, and peak RSS are recorded per suite in the tracked result.
- Not a Pace planner. Pace requires a different intent envelope and product-specific ship gate. Re-distill and evaluate on Pace’s intent envelope before considering any downstream promotion.
- Multi-GB artifact. Weights are ~8 GB and live on Hugging Face Hub, not in git.
How to use
# Metadata check (no weights loaded)
python mlx_load.py
# Load weights into MLX arrays
python mlx_load.py --load
Serve with the PostTrainLLM CLI:
posttrainllm serve --hf-dir ./qwen3-4b-rest-fused
Or load with mlx_lm:
from mlx_lm import load, generate
model, tokenizer = load("posttrainllm/qwen3-4b-rest-fused")
Upload command
This model is already published. To re-upload or update metadata:
# Stage the public metadata surface (no token needed)
python3 scripts/plan_hf_artifact_upload.py \
specialists/qwen3-4b-rest-fused \
--repo-id posttrainllm/qwen3-4b-rest-fused
# Upload to Hugging Face Hub (requires HF login)
huggingface-cli upload posttrainllm/qwen3-4b-rest-fused \
dist/hf-artifacts/qwen3-4b-rest-fused \
--repo-type model
Links
- Project: posttrainllm.com
- Hugging Face repo: posttrainllm/qwen3-4b-rest-fused
- Public artifact page: posttrainllm.com/artifacts/qwen3-4b-rest-fused
- Eval report:
eval_report.json(included in this repo) - Lock file:
tinygpt.lock.json(included in this repo)