Instructions to use Munaza10/ZimageLorawithnocaps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Munaza10/ZimageLorawithnocaps with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("undefined", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Munaza10/ZimageLorawithnocaps") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 4ff17909b19d06531c28761f3df3128212ede80b56268af44fbb7be6f6ea9b65
- Size of remote file:
- 85.1 MB
- SHA256:
- 9fa7565a6c451857c04cdee575a210d1b2c19c326489d8b35ee41b5cd253647b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.