yui-math-python-qwen3.5-4b-v0.5d-fft-GGUF

yui-math-python-qwen35-4b-v0.5d-fft GGUF

GGUF export of naksyu/yui-math-python-qwen35-4b-v0.5d-fft, a full-parameter SFT of Qwen/Qwen3.5-4B for Korean/English math reasoning, Python-assisted calculation habits, and compact practical answers.

Recommended File

Use this file:

This is the intended LM Studio / llama.cpp file for normal local inference.

Compatibility

This model uses the qwen35 GGUF architecture. Use a recent llama.cpp build or an LM Studio build with Qwen3.5 GGUF support.

Important: the source Transformers config contains mtp_num_hidden_layers=1, but the exported checkpoint used here does not contain separate mtp.* tensors. A plain GGUF conversion can produce metadata that expects a non-existent blk.32.* layer and then fail during load.

This GGUF was therefore converted with --no-mtp. The validated metadata is:

llama.cpp Example

CPU load smoke:

llama-server \
  -m yui-math-python-qwen35-4b-v0.5d-fft-no-mtp-Q6_K.gguf \
  --host 127.0.0.1 \
  --port 18080 \
  -c 2048 \
  -ngl 0

Use a larger context only when you have enough RAM/VRAM. The model config advertises 262K context, but this GGUF was only smoke-tested locally at a small context for load compatibility.

LM Studio

In LM Studio, import or place:

yui-math-python-qwen35-4b-v0.5d-fft-no-mtp-Q6_K.gguf

If loading fails, first check that the runtime supports qwen35. If the error mentions missing blk.32.* tensors, it is the MTP metadata mismatch; use the no-mtp-Q6_K file rather than a plain conversion.

Source Model

The source model card is here:

• naksyu/yui-math-python-qwen35-4b-v0.5d-fft

Base model:

• Qwen/Qwen3.5-4B

Training Data Summary

The source checkpoint was trained on qwen35_sft_v0_5d_system_mix_with_all_data_cutoff2048.jsonl.

Public data sources included:

• drlee1/deepseek-v4-distill-ko-1k
• Jackrong/DeepSeek-V4-Distill-8000x
• Jackrong/GLM-5.1-Reasoning-1M-Cleaned
• Jongsim/claude-opus-4.6-reasoning-12k-ko-filtered-v2
• Roman1111111/claude-opus-4.6-10000x
• nohurry/Opus-4.6-Reasoning-3000x-filtered
• TeichAI/claude-4.5-opus-high-reasoning-250x

Limitations

• Experimental local SFT conversion, not a benchmarked production release.
• Q6_K quantization changes numerical behavior from the bf16 source checkpoint.
• Requires current GGUF runtime support for Qwen3.5 / qwen35.
• The model can still make arithmetic, reasoning, and code mistakes. Verify important outputs externally.

Training Data

This model was fine-tuned for experimental math/Python reasoning behavior.

The training mix includes:

• User-created Lime/Yui math-python SFT data
• Public Hugging Face datasets including:
  • drlee1/deepseek-v4-distill-ko-1k (MIT)
  • Jongsim/claude-opus-4.6-reasoning-12k-ko-filtered-v2 (Apache-2.0)

Some upstream samples are synthetic or translated model outputs. This release is intended as a research/experimental small-model fine-tune, not as a commercial substitute for the upstream model providers.