Compact, capable language model for fast inference, part of the OSS-clean Zen model line.
Repackaged from
Qwen/Qwen3-8B (apache-2.0, Alibaba Qwen).
Not trained from scratch — a permissively-licensed redistribution for the OSS-clean Zen model line.
1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3model = AutoModelForCausalLM.from_pretrained("zenlm/zen3-nano", torch_dtype="auto")
4tokenizer = AutoTokenizer.from_pretrained("zenlm/zen3-nano")
5
6messages = [{"role": "user", "content": "Explain quantum computing in simple terms."}]
7text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
8inputs = tokenizer([text], return_tensors="pt").to(model.device)
9outputs = model.generate(**inputs, max_new_tokens=512)
10print(tokenizer.decode(outputs[0], skip_special_tokens=True))
1from openai import OpenAI
2
3client = OpenAI(base_url="https://api.hanzo.ai/v1", api_key="YOUR_KEY")
4response = client.chat.completions.create(
5 model="zen3-nano",
6 messages=[{"role": "user", "content": "Hello"}],
7)
8print(response.choices[0].message.content)
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