Instructions to use antonellaavad/daniel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use antonellaavad/daniel with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1-base", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("antonellaavad/daniel") prompt = "ohxs" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- ee58d3289160b80b823370d6d56b9aaeca5499f1641995c4bc2cb6d9ba4cdb1a
- Size of remote file:
- 3.49 MB
- SHA256:
- 261d95d25b8133a7a294df6d80019eea54db3f86c19925e6db19d5e5437f4244
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.