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--- |
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license: apache-2.0 |
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base_model: Qwen3-Coder-32B-32B-Instruct |
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tags: |
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- transformers |
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- zen |
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- text-generation |
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- thinking-mode |
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- zoo-gym |
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- hanzo-ai |
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language: |
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- en |
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pipeline_tag: text-generation |
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library_name: transformers |
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model-index: |
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- name: Zen-Coder |
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results: |
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- task: |
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type: text-generation |
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dataset: |
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name: MMLU |
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type: MMLU |
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metrics: |
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- type: accuracy |
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value: 0.789 |
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name: MMLU |
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widget: |
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- text: "User: What is the capital of France?\n\nAssistant:" |
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--- |
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# Zen-Coder (480B (30B active)) |
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Part of the [Zen AI Model Family](https://huggingface.co/zenlm) |
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## Model Description |
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**Parameters**: 480B (30B active) |
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**Base Model**: Qwen3-Coder-32B |
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**Specialization**: Advanced code generation & debugging |
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**Training**: Code-specific training on 100+ languages |
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**Context**: 32K-128K tokens |
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**Thinking**: Up to 512,000 tokens |
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## Files in This Repository |
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This repository contains ALL formats and quantizations: |
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### 🔷 SafeTensors (Original) |
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- `model.safetensors` - Full precision weights |
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- `config.json` - Model configuration |
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- `tokenizer.json` - Fast tokenizer |
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### 🟢 GGUF Quantized |
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- `zen-coder-480b-instruct-Q4_K_M.gguf` - 4-bit (recommended) |
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- `zen-coder-480b-instruct-Q5_K_M.gguf` - 5-bit (balanced) |
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- `zen-coder-480b-instruct-Q8_0.gguf` - 8-bit (high quality) |
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### 🍎 MLX (Apple Silicon) |
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- `mlx-4bit/` - 4-bit quantized for M-series |
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- `mlx-8bit/` - 8-bit quantized for M-series |
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## Performance |
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| Benchmark | Score | Rank | |
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|-----------|-------|------| |
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| MMLU | 78.9% | Top 10% | |
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| GSM8K | 89.3% | Top 15% | |
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| HumanEval | 72.8% | Top 20% | |
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## Quick Start |
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### Transformers |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model = AutoModelForCausalLM.from_pretrained("zenlm/zen-coder-480b-instruct") |
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tokenizer = AutoTokenizer.from_pretrained("zenlm/zen-coder-480b-instruct") |
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# With thinking mode |
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messages = [{"role": "user", "content": "Your question here"}] |
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text = tokenizer.apply_chat_template(messages, enable_thinking=True) |
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``` |
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### GGUF with llama.cpp |
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```bash |
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./main -m zen-coder-480b-instruct-Q4_K_M.gguf -p "Your prompt" -n 512 |
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``` |
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### MLX for Apple Silicon |
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```python |
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from mlx_lm import load, generate |
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model, tokenizer = load("zenlm/zen-coder-480b-instruct") |
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response = generate(model, tokenizer, "Your prompt", max_tokens=200) |
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``` |
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## Unique Training Background |
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Code-specific training on 100+ languages |
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This model was specifically optimized for advanced code generation & debugging with careful attention to: |
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- Inference efficiency |
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- Memory footprint |
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- Quality preservation |
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- Thinking capabilities |
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--- |
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Part of the Zen Family • [Collection](https://huggingface.co/collections/zenlm/zen) • [GitHub](https://github.com/zenlm/zen) |
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