Instructions to use pcuenq/pokemon-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use pcuenq/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("pcuenq/pokemon-lora", dtype=torch.bfloat16, device_map="cuda") 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-3500/scheduler.bin from pcuenq/pokemon-lora: direct link, hf CLI and curl.
- Browser
- Download file 563 Bytes
-
https://huggingface.co/pcuenq/pokemon-lora/resolve/main/checkpoint-3500/scheduler.bin
- Command line
-
hf download hf://pcuenq/pokemon-lora/checkpoint-3500/scheduler.bin
-
curl -L -o scheduler.bin https://huggingface.co/pcuenq/pokemon-lora/resolve/main/checkpoint-3500/scheduler.bin
563 Bytes
- Xet hash:
- 45ccee8c5ac55b9b5be6a14ee86e50d41aa54729b6d4a768533b97da637f80c6
- Size of remote file:
- 563 Bytes
- SHA256:
- 12b08cbd665f3376fc3303ead0c205c01f368f2142f5ce3cc62bb1f6a1d7d2ef
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