Instructions to use bodam/model_lora2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bodam/model_lora2 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("bodam/model_lora2") prompt = "a s3f chair" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 7cbb32e62c5d42380e1edc368aa774fc66a108639135d71c26d0ccd480945c40
- Size of remote file:
- 6.59 MB
- SHA256:
- 3d4123aae07cf966ebe63f33f5353f567edb86d3f2075d3e2b52e2575eedeb93
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