gemma-4-E4B-it-Coder-GGUF

Gemma-4-E4B-it-Coder GGUF

GGUF exports of josephmayo/gemma-4-E4B-it-Coder, a merged coding-focused fine-tune of google/gemma-4-E4B-it.

Files

50-Problem HumanEval Proof

Evaluated on Kaggle with 2x Tesla T4 GPUs using an executable 50-task HumanEval subset. Full generated before/after code is published in eval50_before_after_full_code.csv.

Proof files: eval50_summary.json, eval50_before_after_full_code.csv, EVAL50_README.md, nvidia_smi.txt.

Local GGUF sanity check was run with llama.cpp b9133 on CPU. The Q3_K_M file loaded and generated a simple Python add(a, b) implementation. CPU speed was slow on this Windows machine, around 0.8 tokens/s, so use GPU llama.cpp, LM Studio, Ollama, or another accelerated runtime for normal use.

Example

llama-cli -m Gemma-4-E4B-it-Coder-Q5_K_M.gguf   -p "Write a Python function is_prime(n). Return only code."   -n 256 --temp 0.2 --ctx-size 2048

Notes

• This repository publishes the quantized runtime artifacts only.
• The merged HF safetensors model is available at josephmayo/gemma-4-E4B-it-Coder.
• Training data details are intentionally summarized as filtered benign coding instruction data.

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Evidence files

Run evidence for this release is stored in the repository under evidence/:

• evidence/holykeys_gemma4_sft_output_release_release_summary.json

These files are compact local/Kaggle run artifacts used to document training, evaluation, merge, or quantization evidence for this model family.

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