Instructions to use stillerman/poke-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stillerman/poke-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("stillerman/poke-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-200/pytorch_model.bin from stillerman/poke-lora: direct link, hf CLI and curl.
- Browser
- Download file 3.29 MB
-
https://huggingface.co/stillerman/poke-lora/resolve/main/checkpoint-200/pytorch_model.bin
- Command line
-
hf download hf://stillerman/poke-lora/checkpoint-200/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/stillerman/poke-lora/resolve/main/checkpoint-200/pytorch_model.bin
3.29 MB
- Xet hash:
- 195ed85571cec4449fbe02b5dc749b612c51d440563d55a903e895fb2b5d9d6d
- Size of remote file:
- 3.29 MB
- SHA256:
- 054ad7fa4056b83abb1d2779ba43976176efe869380a9e93d438a109f6d546de
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