posttrainllm

qwen3-4b-file-ops-distilled

README

License: apache-2.0

Summary

This is the first posttrainllm specialist package for a model we actually built: a fused Qwen3-4B-Instruct-2507 bf16 HF/MLX safetensors directory distilled for GorillaFileSystem multi-turn file-operation tasks.

It is a routed specialist, not the general Pace planner.

Artifact

Package id: qwen3-4b-file-ops-distilled
Public artifact: posttrainllm/qwen3-4b-file-ops-distilled
Public storage target: Hugging Face Hub model repo
Format: HF/MLX safetensors directory
Base: Qwen/Qwen3-4B-Instruct-2507
Precision: bf16
Training method: frontier/gold trajectory distillation rendered in the student's native tool-calling chat template

Measured Result

Table with columns: Suite, Stock 4B, Distilled 4B
Suite	Stock 4B	Distilled 4B
File-ops hard gate	58%	100%
File-ops hardgen held-out	-	95%
Out-of-domain breadth	59.6%	42.3%

The file-ops domain saturated at 4B: the distilled model matched frontier on the hard and veryhard file-ops gates. The same training caused negative transfer outside that domain, so this package is only correct behind a router.

Recommended Use

Use this model when the router has already identified a file-operation task with derivable arguments: paths, file names, directories, moves, creates, deletes, and navigation through a file-system backend.

Do not use it as a general planner. For general multi-domain planning, use the planner lock in docs/sessions/planner-lock-2026-06-19.md: stock Qwen3-4B-Instruct-2507 bf16 with the plan-then-execute prompt.

Known Limits

The specialist regresses on non-filesystem BFCL multi-turn backends.
It was not validated as a broad Pace planner.
It depends on correct routing. Bad routing turns a narrow win into a broad regression.
The artifact is multi-GB and is published on Hugging Face Hub, not committed to this repository or required to remain in local cache.

License and provenance

Weights are derived from Qwen/Qwen3-4B-Instruct-2507, published under Apache-2.0. This package is distributed under the same Apache-2.0 license.
Training data: ~99 checker-passing DeepSeek-V4-pro rollouts over synthetic, templated GorillaFileSystem tasks authored by this repository (rejection-sampled SFT rendered in the student's chat template). An identical model was independently reproduced with teacher-free gold behaviour-cloning; see docs/learn/tool-calling-frontier-parity.md §8.1.
The distributed artifact is itself fused Qwen-derived weights; no BFCL datasets, teacher trajectories, or additional third-party weights are bundled. The evaluation methodology derives from Berkeley's BFCL multi-turn suite (Apache-2.0).

References

Project and learning lab
Mac quickstart
Distillation recipe
Evidence and limitations
Base model and license
docs/learn/tool-calling-frontier-parity.md sections 8.1-8.5
docs/sessions/planner-lock-2026-06-19.md

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Model Details

Model Provider

posttrainllm

Model Tree

Base

Qwen/Qwen3-4B-Instruct-2507

Fine-tuned

this model

Input Modalities

Text

Output Modalities