Instructions to use yunhaif/ReflectVLM-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yunhaif/ReflectVLM-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("yunhaif/ReflectVLM-diffusion", 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
- Xet hash:
- b8cae1eef184ea572515334570ea3b3861f6f5800e72dc5fe1e9d07e639df993
- Size of remote file:
- 167 MB
- SHA256:
- bb30356d9df425e1922a3975c3d0e31dd8130833f0af00ab08d6da780a2963fe
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