Instructions to use zenlm/zen-world with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zenlm/zen-world with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("zenlm/zen-world", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Zen World
World simulation model for interactive environment generation.
Overview
Built on Zen MoDE (Mixture of Distilled Experts) architecture with 13B parameters.
Developed by Hanzo AI and the Zoo Labs Foundation.
Quick Start
from diffusers import AutoPipelineForText2Video
import torch
model_id = "zenlm/zen-world"
pipe = AutoPipelineForText2Video.from_pretrained(model_id, torch_dtype=torch.bfloat16)
pipe = pipe.to("cuda")
video_frames = pipe("A drone flying over a tropical coastline at golden hour").frames[0]
API Access
from openai import OpenAI
client = OpenAI(base_url="https://api.hanzo.ai/v1", api_key="your-api-key")
response = client.images.generate(
model="zen-world",
prompt="A drone flying over a tropical coastline at golden hour",
size="1280x720",
)
print(response.data[0].url)
Model Details
| Attribute | Value |
|---|---|
| Parameters | 13B |
| Architecture | Zen MoDE |
| License | Apache 2.0 |
License
Apache 2.0
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