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-1000/scaler.pt from AACEE/pokemon-lora: direct link, hf CLI and curl.
- Browser
- Download file 557 Bytes
-
https://huggingface.co/AACEE/pokemon-lora/resolve/main/checkpoint-1000/scaler.pt
- Command line
-
hf download hf://AACEE/pokemon-lora/checkpoint-1000/scaler.pt
-
curl -L -o scaler.pt https://huggingface.co/AACEE/pokemon-lora/resolve/main/checkpoint-1000/scaler.pt
557 Bytes
- Xet hash:
- b7f6dc893c0aa31fa33689c92b8ef4d5030e9722973defe1275a56b33fdc45a0
- Size of remote file:
- 557 Bytes
- SHA256:
- 68cff80b680ddf6e7abbef98b5f336b97f9b5963e2209307f639383870e8cc71
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