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:
- 25aeb2151804c69e847a6315f62e14262f46c1f28e971a04fda2cc03246d4fe1
- Size of remote file:
- 6.58 MB
- SHA256:
- b6a1b389cf9c50347e7378dd14c7f9a0c0380daa5d34802ceb926ae77148a45d
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