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-5000/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-5000/optimizer.bin
- Command line
-
hf download hf://HGYash/jojo-lora/checkpoint-5000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/HGYash/jojo-lora/resolve/main/checkpoint-5000/optimizer.bin
3.4 MB
- Xet hash:
- ec4522e03b508862d7e4045d295965175837d14a64ab2146cef6a1eea608910f
- Size of remote file:
- 3.4 MB
- SHA256:
- 932e14f93a9fed12f07533cf682de541f919014f127813a9b4ba1d9ecf1f6212
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