Instructions to use bchao1/foveated_diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bchao1/foveated_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("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("bchao1/foveated_diffusion") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Upload foveated_diffusion image LoRAs
Browse files- image/fov_bbox.safetensors +3 -0
- image/fov_random.safetensors +3 -0
- image/fov_saliency.safetensors +3 -0
- image/no_fov.safetensors +3 -0
- video/.gitkeep +0 -0
image/fov_bbox.safetensors
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video/.gitkeep
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