Text-to-Image
Diffusers
TensorBoard
lora
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use codeiceman/rice-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codeiceman/rice-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("codeiceman/rice-model") prompt = "a photo of tasty rice" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 5f574671e87e099d96713cbfd4a6fafed1ec6f4f99a36deec1ad36872c0fed99
- Size of remote file:
- 3.23 MB
- SHA256:
- e491ff5b4a369801db629fb7c836c51e4f9046ceaff04034ce7141c6139a9721
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.