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-8500/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-8500/optimizer.bin
- Command line
-
hf download hf://AACEE/pokemon-lora/checkpoint-8500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/AACEE/pokemon-lora/resolve/main/checkpoint-8500/optimizer.bin
6.59 MB
- Xet hash:
- 3da4a64e5a64d205aa6cbc9a384415770441711d3620f0565e5f7c11bf6d3087
- Size of remote file:
- 6.59 MB
- SHA256:
- db3812e97eddf61770018efeeef99cc1321d1495f906a0f434d62a1e9061e060
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