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-8000/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-8000/scheduler.bin
- Command line
-
hf download hf://pcuenq/pokemon-lora/checkpoint-8000/scheduler.bin
-
curl -L -o scheduler.bin https://huggingface.co/pcuenq/pokemon-lora/resolve/main/checkpoint-8000/scheduler.bin
563 Bytes
- Xet hash:
- 63032cdbcf4dd9b769d09e3c59498eb6237855a78b508878ee9ab70c5515971e
- Size of remote file:
- 563 Bytes
- SHA256:
- f502fef00d7f4f00f5cd3d95b0ceeeb3107b302c03c7de138f15d9aeeaa30e4c
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