| --- |
| base_model: vsan/tiny-pickle-v3-coder |
| library_name: mlx |
| pipeline_tag: text-generation |
| license: apache-2.0 |
| tags: |
| - mlx |
| - qwen3-coder |
| - coding |
| - software-engineering |
| - quantized |
| - 4bit |
| - apple-silicon |
| - moe |
| - tiny-pickle |
| --- |
| |
| # Tiny Pickle v3 Coder — MLX 4-bit |
|
|
| Tiny Pickle v3 Coder is a coding-focused adaptation of |
| `Qwen/Qwen3-Coder-30B-A3B-Instruct`, converted to MLX and quantized for |
| Apple Silicon. |
|
|
| ## Model lineage |
|
|
| - Base model: `Qwen/Qwen3-Coder-30B-A3B-Instruct` |
| - LoRA adapter: `vsan/tiny-pickle-v3-coder-LoRA` |
| - Merged Safetensors: `vsan/tiny-pickle-v3-coder` |
| - Quantization: MLX affine 4-bit |
| - Group size: 64 |
| - Converted directory size: 16G |
|
|
| ## Installation |
|
|
| ```bash |
| pip install -U mlx-lm |
| ``` |
|
|
| ## Interactive chat |
|
|
| ```bash |
| mlx_lm.chat --model mlx-community/Tiny-Pickle-v3-Coder-4bit |
| ``` |
|
|
| ## Command-line generation |
|
|
| ```bash |
| mlx_lm.generate \ |
| --model mlx-community/Tiny-Pickle-v3-Coder-4bit \ |
| --prompt "Write a tested Python implementation of an LRU cache." \ |
| --max-tokens 800 |
| ``` |
|
|
| ## Intended use |
|
|
| Code generation, debugging, code review, implementation planning, test |
| generation, and local software-engineering assistance on Apple Silicon. |
|
|
| ## Quantization |
|
|
| This release uses MLX 4-bit affine quantization with group size 64. |
| Quantization reduces storage and unified-memory requirements but may alter |
| outputs or reduce quality relative to the merged BF16 model. |
|
|
| ## Limitations |
|
|
| Tiny Pickle v3 Coder is experimental and has not yet been independently |
| demonstrated to outperform its base model. Generated code may be incorrect, |
| insecure, incomplete, or non-functional and must be reviewed and tested. |
|
|
| ## Related repositories |
|
|
| - LoRA: https://huggingface.co/vsan/tiny-pickle-v3-coder-LoRA |
| - Merged Safetensors: https://huggingface.co/vsan/tiny-pickle-v3-coder |
| - GGUF: https://huggingface.co/vsan/tiny-pickle-v3-coder-GGUF |
|
|
| ## Local Performance |
|
|
| The following result is a single local inference measurement, not a standardized benchmark. |
|
|
| | Property | Result | |
| |---|---:| |
| | Hardware | Apple M1 Max | |
| | Unified memory | 64 GB | |
| | Model format | MLX 4-bit affine | |
| | Quantization group size | 64 | |
| | Prompt length | 118 tokens | |
| | Prompt processing speed | 119.328 tokens/s | |
| | Generated length | 748 tokens | |
| | Generation speed | 63.481 tokens/s | |
| | Peak unified memory | 17.393 GB | |
|
|
| ### Test prompt |
|
|
| > You are reviewing a Python async web crawler. Implement a complete, production-quality crawler that uses asyncio and aiohttp; limits global concurrency to 20; limits each domain to 2 concurrent requests; respects robots.txt; retries HTTP 429 and 5xx responses with exponential backoff and jitter; avoids duplicate URLs; normalizes relative links; restricts crawling to the starting domain; supports cancellation; records failures without stopping the crawl; and includes pytest tests using mocked HTTP responses. Return one self-contained Python module followed by the tests. |
|
|
| Results can vary with the macOS version, MLX-LM version, background processes, context length, sampling configuration, and thermal state. |
|
|
