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-4000/optimizer.bin from pcuenq/pokemon-lora: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/pcuenq/pokemon-lora/resolve/main/checkpoint-4000/optimizer.bin
- Command line
-
hf download hf://pcuenq/pokemon-lora/checkpoint-4000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/pcuenq/pokemon-lora/resolve/main/checkpoint-4000/optimizer.bin
6.59 MB
- Xet hash:
- a604ab5c94269706f58b25fcac10f8826a8c3a4f6d9c7cd7e5d30cda70f1ee16
- Size of remote file:
- 6.59 MB
- SHA256:
- 87cce0f8b7ac8c3ec94ab76bde84871190820e8720bc9eff075108357bf9fe29
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