bash2nl โ€” Qwen2.5-Coder-3B QLoRA, GGUF q4_K_M

Explains a Bash command line in exactly one English sentence, phrased as an instruction starting with a verb. QLoRA fine-tune of Qwen/Qwen2.5-Coder-3B-Instruct, merged and quantized to q4_K_M.

find . -name "*.py"
-> Find all *.py files/directories under current directory

Usage

hf download C-H-Liu/bash2nl-qwen2.5-coder-3b-GGUF --local-dir bash2nl-3b
cd bash2nl-3b && ollama create bash2nl-3b -f Modelfile
ollama run bash2nl-3b 'ps -ef | grep nginx | awk "{print \$2}" | xargs kill -9'

The Modelfile pins the system prompt and this decoding:

option value
temperature 0.0
top_k 1
top_p 1.0
repeat_penalty 1.0
num_predict 96
num_ctx 4096
stop `<

Evaluation

920 held-out commands Judge columns are claude-sonnet-5 scoring a fixed 200-command subset.

metric 3B base 3B qlora f16 3B qlora q4_K_M, no examples this model 7B qlora q4_K_M
BLEU 13.49 32.04 32.04 32.30 33.49
chrF 43.12 50.85 50.81 50.39 52.21
ROUGE-L 37.58 51.91 51.37 51.19 53.24
judge acceptable+ 0.785 0.890 0.825 0.875 0.890
judge wrong 0.215 0.110 0.175 0.125 0.110
avg words 18.5 11.8 11.9 11.9 12.4

License

Apache-2.0, matching the base model, whose weights this GGUF contains. Training data comes from the nl2bash project; consult it for the terms attached to that corpus.

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