Instructions to use Jingya/tiny-qwen-image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jingya/tiny-qwen-image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Jingya/tiny-qwen-image", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 6e8257ef688684902884fd4cdbecef837f5094dfc3df3a81484ccd111b59ba10
- Size of remote file:
- 11.4 MB
- SHA256:
- e24d28c0a7e2c08dcc0486e3f243ececb8b7c4abf6064fb863f1d0fc92ef9309
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