Instructions to use jafetsierra/rem_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jafetsierra/rem_output 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("jafetsierra/rem_output") prompt = "a picture of rem a girl character from re zero. she wears a maid costume, has blue eyes and a big breast" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- c2f873ae1637c0b10929b0a5902059f996c02ce43d4fc885026257e21e806ad2
- Size of remote file:
- 1 kB
- SHA256:
- 1ce60e6ec914ae38ef1ad81ab543485464fcd4e4fbe8f218f4296e04695c4cc2
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