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:
- 9388653b53c3de3b5a10b09ac9088ecb49609779213d7a9d63d350b54e4c4ee2
- Size of remote file:
- 6.58 MB
- SHA256:
- ebd1b29fefbae6b06bab138dae3735dee71e7d7e5c232627dce24e808346ab47
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