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:
- 46a05fa65909c81f1be5098292822ae309799376ddc309ca31f01dc64c2cb795
- Size of remote file:
- 6.58 MB
- SHA256:
- aaba39cdef99e0c087f66ea406223092ef5df8a43ce0babcaa247a60eb041375
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