Text-to-Image
Diffusers
Safetensors
stable-diffusion
stable-diffusion-diffusers
diffusers-training
lora
Instructions to use HGYash/jojo-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use HGYash/jojo-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("HGYash/jojo-lora") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-2000/optimizer.bin from HGYash/jojo-lora: direct link, hf CLI and curl.
- Browser
- Download file 3.4 MB
-
https://huggingface.co/HGYash/jojo-lora/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://HGYash/jojo-lora/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/HGYash/jojo-lora/resolve/main/checkpoint-2000/optimizer.bin
3.4 MB
- Xet hash:
- 8c7196b63ec27bdf09dc9362f6643819f4fd76f033b027ad33bd8ada32f4ca1e
- Size of remote file:
- 3.4 MB
- SHA256:
- e4b341251e5a20960ed86d99a1b9434dd9dc659e55c5f1e80457dff63c0d8e53
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