Instructions to use samarthum/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use samarthum/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("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("samarthum/model") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 76b06907457c99beb03b223eb89fcabbb190b5ab046d9ac781f327c39a9619dd
- Size of remote file:
- 6.59 MB
- SHA256:
- b790b131651a47283c60a926d45c12a5fe11345dd489a02db9d1e76d86701d5f
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