Qwen3-0.6B-lk-alpha-14b-paired-MNN

Experimental Qwen3-0.6B draft model for TokForge + MNN, trained as a more target-paired draft for Qwen3-14B style use.

Why this repo exists

Most mobile draft work ends up optimized around 8B. This repo exists for the opposite question:

what happens if a very small draft is trained more explicitly toward a 14B target lane?

Training snapshot

Final logged training acceptance (alpha):

  • 0.7236

Usage

This bundle is meant for TokForge / MNN, not standard HF Inference.

Typical TokForge recipe:

{
  "backend_type": "cpu",
  "thread_num": 4,
  "precision": "low",
  "memory": "low",
  "sampler_type": "greedy",
  "speculative_type": "draftmodel",
  "draft_predict_length": 3,
  "draft_config_path": "/path/to/config_cpu.json"
}

Status

This is a research / targeted pairing artifact:

  • intended for 14B-leaning experiments
  • more specialized than the general 20K 8B draft lane
  • not yet the default recommendation over the simpler general-purpose drafts

Limitations and Intended Use

  • This is a target-paired experiment, not the current default draft recommendation.
  • Best treated as a research option for 14B-leaning mobile tests.
  • General-purpose users should usually start with the 20K baseline draft first.

Collection

Best-known use

  • Draft model backend: CPU
  • Draft threads: 2
  • Draft predict length: d=3
  • Intended target pairing: Qwen3-14B in TokForge

Included files

  • llm.mnn
  • llm.mnn.weight
  • llm_config.json
  • config.json
  • config_cpu.json
  • tokenizer files
  • ONNX export artifact for reference

TokForge

If you benchmark this on your own device, feel free to share results in Discord.

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