vsan/tiny-pickle-v3-coder-GGUF

Tiny Pickle v3 Coder — GGUF

Quantized GGUF releases of Tiny Pickle v3 Coder.

Tiny Pickle v3 Coder was produced by fine-tuning Qwen/Qwen3-Coder-30B-A3B-Instruct with the LoRA adapter published at vsan/tiny-pickle-v3-coder-LoRA, then merging and converting the resulting model with llama.cpp.

Files

File	Quantization	Approximate size
tiny-pickle-v3-coder-q8_0.gguf	Q8_0	31G
tiny-pickle-v3-coder-q4_k_m.gguf	Q4_K_M	18G

Q8_0 retains greater numerical fidelity but requires more storage and memory. Q4_K_M is smaller and more practical for local inference.

Run with llama.cpp

llama-cli \
  -m tiny-pickle-v3-coder-q4_k_m.gguf \
  -ngl 99 \
  -c 8192 \
  -p "Write a robust Python LRU cache with unit tests."

Intended use

• Code generation
• Debugging
• Code review
• Implementation planning
• Test generation
• Software-engineering assistance

Limitations

Tiny Pickle v3 Coder is experimental and has not yet been proven superior to its base model on independent benchmarks. Quantization may reduce model quality. Generated code can be incorrect, insecure, incomplete, or non-functional and must be reviewed and tested.