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", torch_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
| from ...utils import ( | |
| OptionalDependencyNotAvailable, | |
| is_flax_available, | |
| is_torch_available, | |
| is_transformers_available, | |
| ) | |
| try: | |
| if not (is_transformers_available() and is_torch_available()): | |
| raise OptionalDependencyNotAvailable() | |
| except OptionalDependencyNotAvailable: | |
| from ...utils.dummy_torch_and_transformers_objects import * # noqa F403 | |
| else: | |
| from .multicontrolnet import MultiControlNetModel | |
| from .pipeline_controlnet import StableDiffusionControlNetPipeline | |
| from .pipeline_controlnet_img2img import StableDiffusionControlNetImg2ImgPipeline | |
| from .pipeline_controlnet_inpaint import StableDiffusionControlNetInpaintPipeline | |
| from .pipeline_controlnet_sd_xl import StableDiffusionXLControlNetPipeline | |
| if is_transformers_available() and is_flax_available(): | |
| from .pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline | |