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zenlm
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zenlm
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Built on Zen MoDE (Mixture of Distilled Experts) architecture with 30B MoE parameters and 128K context window.
Developed by Hanzo AI and the Zoo Labs Foundation.
python
from transformers import AutoModelForVision2Seq, AutoProcessorfrom PIL import Imageimport torch model_id = "zenlm/zen-omni-30b-thinking"processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)model = AutoModelForVision2Seq.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto", trust_remote_code=True) messages = [ {"role": "user", "content": "Describe this image in detail."}] # Text-onlytext = processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)inputs = processor(text=[text], return_tensors="pt").to(model.device)outputs = model.generate(**inputs, max_new_tokens=512)print(processor.batch_decode(outputs, skip_special_tokens=True)[0])python
from openai import OpenAI client = OpenAI(base_url="https://api.hanzo.ai/v1", api_key="your-api-key")response = client.chat.completions.create( model="zen-omni-30b-thinking", messages=[{"role": "user", "content": "Hello!"}],)print(response.choices[0].message.content)| Attribute | Value |
|---|---|
| Parameters | 30B MoE |
| Architecture | Zen MoDE |
| Context | 128K tokens |
| License | Apache 2.0 |
Apache 2.0
from transformers import AutoModelForVision2Seq, AutoProcessorfrom PIL import Imageimport torch model_id = "zenlm/zen-omni-30b-thinking"processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)model = AutoModelForVision2Seq.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto", trust_remote_code=True) messages = [ {"role": "user", "content": "Describe this image in detail."}] # Text-onlytext = processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)inputs = processor(text=[text], return_tensors="pt").to(model.device)outputs = model.generate(**inputs, max_new_tokens=512)print(processor.batch_decode(outputs, skip_special_tokens=True)[0])