Zen Coder
Code generation and analysis model family spanning 4B to 480B parameters.
Overview
Built on Zen MoDE (Mixture of Distilled Experts) architecture with 4B–480B parameters and 128K context window.
Developed by Hanzo AI and the Zoo Labs Foundation.
Quick Start
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "zenlm/zen-coder"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto")
messages = [{"role": "user", "content": "Hello!"}]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer([text], return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True))
API Access
curl https://api.hanzo.ai/v1/chat/completions \
-H "Authorization: Bearer $HANZO_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model": "zen-coder", "messages": [{"role": "user", "content": "Hello"}]}'
Get your API key at console.hanzo.ai — $5 free credit on signup.
Model Details
| Attribute | Value |
|---|---|
| Parameters | 4B–480B |
| Architecture | Zen MoDE |
| Context | 128K tokens |
| License | Apache 2.0 |
License
Apache 2.0
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