Instructions to use AACEE/pokemon-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AACEE/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("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("AACEE/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 checkpoint-2000/optimizer.bin from AACEE/pokemon-lora: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/AACEE/pokemon-lora/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://AACEE/pokemon-lora/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/AACEE/pokemon-lora/resolve/main/checkpoint-2000/optimizer.bin
6.59 MB
- Xet hash:
- 9813379a931ca5f60e834a32625a212208518fa4f6e76bac236402d269decaa9
- Size of remote file:
- 6.59 MB
- SHA256:
- 52c2af6c758a75e76117a64534d607885169842d32596ea96aacfb52dff590ee
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