Instructions to use mikephillips/pokemon-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mikephillips/pokemon-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("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("mikephillips/pokemon-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 image_0.png from mikephillips/pokemon-lora: direct link, hf CLI and curl.
- Browser
- Download file 381 kB
-
https://huggingface.co/mikephillips/pokemon-lora/resolve/main/image_0.png
- Command line
-
hf download hf://mikephillips/pokemon-lora/image_0.png
-
curl -L -o image_0.png https://huggingface.co/mikephillips/pokemon-lora/resolve/main/image_0.png
381 kB

- Xet hash:
- 2c037fad1cc740bba662a33af1f727ca9c86dc748a73e8ffa12ea75ff7f92f6d
- Size of remote file:
- 381 kB
- SHA256:
- 78d5865790386ed8657755c7bdcf77f6c46d89bf54f6786076f31d4fb89574c7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.