Instructions to use deepgoyal19/lora4_tb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use deepgoyal19/lora4_tb with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("deepgoyal19/lora4_tb") 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
- Xet hash:
- ca926e5d6827f892ea2969e27f81cbea3d6b15aaeed7758ee1c85081b8d13c6f
- Size of remote file:
- 3.29 MB
- SHA256:
- abf696df68ad5905c8a4df2f94588880b78bf5f043ed2eed70bcfcb5c1794705
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