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
- Draw Things
- DiffusionBee
- altdiffusion
- audio_diffusion
- audioldm
- consistency_models
- controlnet
- dance_diffusion
- ddim
- ddpm
- deepfloyd_if
- dit
- kandinsky
- kandinsky_v22
- karras_ve
- latent_diffusion
- paint_by_example
- pndm
- repaint
- score_sde_ve
- semantic_stable_diffusion
- shap_e
- spectrogram_diffusion
- stable_diffusion
- stable_diffusion_2
- stable_diffusion_safe
- stable_diffusion_xl
- stable_unclip
- text_to_video
- unclip
- unidiffuser
- versatile_diffusion
- vq_diffusion
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