Text-to-Image
Diffusers
TensorBoard
Safetensors
stable-diffusion
stable-diffusion-diffusers
diffusers-training
lora
Instructions to use animanatwork/illustrations-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use animanatwork/illustrations-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("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("animanatwork/illustrations-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-3000/optimizer.bin from animanatwork/illustrations-lora: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/animanatwork/illustrations-lora/resolve/main/checkpoint-3000/optimizer.bin
- Command line
-
hf download hf://animanatwork/illustrations-lora/checkpoint-3000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/animanatwork/illustrations-lora/resolve/main/checkpoint-3000/optimizer.bin
6.59 MB
- Xet hash:
- cd1e87a9b02213d2e69ef23e7300d125f26688d408eb0bbcf739a049239eb46b
- Size of remote file:
- 6.59 MB
- SHA256:
- 3ec47aec8e92e62d17d8b3b5fd3f58a323ba08847e51e64447038cccf05085bf
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