Instructions to use mathieuripert/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mathieuripert/model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("mathieuripert/model") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- a880c53cefffc4130e3ed393ba808568fd256aa1c9c076a036eeb09b8bd809be
- Size of remote file:
- 6.58 MB
- SHA256:
- 2d6d0d53a1374059c9f68a93da23e08c3938bf5a0b8f61209ada28d23d656a76
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