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

Downloads last month
30
Safetensors
Model size
31B params
Tensor type
BF16
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