metadata
license: apache-2.0
language:
- en
- zh
tags:
- zen4
- zenlm
- hanzo
- abliterated
- uncensored
base_model: huihui-ai/Huihui-Qwen3-Coder-Next-abliterated
pipeline_tag: text-generation
Zen4 Coder
Zen4 Coder is a 80B MoE (3B active) parameter language model from the Zen4 family by Zen LM and Hanzo AI.
Built on abliterated (uncensored) weights from Qwen3-Coder-Next for unrestricted, open-ended AI assistance.
Model Details
| Property | Value |
|---|---|
| Parameters | 80B MoE total, 3B active |
| Context | 256K tokens |
| Base | Qwen3-Coder-Next (abliterated) |
| License | Apache-2.0 |
| Family | Zen4 |
| Creator | Zen LM / Hanzo AI |
Zen4 Family
| Model | Params | Active | Context | HuggingFace |
|---|---|---|---|---|
| Zen4 Mini | 4B | 4B | 32K | zenlm/zen4-mini |
| Zen4 | 8B | 8B | 32K | zenlm/zen4 |
| Zen4 Pro | 14B | 14B | 32K | zenlm/zen4-pro |
| Zen4 Max | 30B MoE | 3B | 256K | zenlm/zen4-max |
| Zen4 Pro Max | 80B MoE | 3B | 256K | zenlm/zen4-pro-max |
| Zen4 Coder Flash | 31B MoE | 3B | 131K | zenlm/zen4-coder-flash |
| Zen4 Coder | 80B MoE | 3B | 256K | zenlm/zen4-coder |
| Zen4 Ultra | 1.04T MoE | 32B | 256K | zenlm/zen4-ultra |
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("zenlm/zen4-coder")
tokenizer = AutoTokenizer.from_pretrained("zenlm/zen4-coder")
messages = [{"role": "user", "content": "Hello, who are you?"}]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))