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
| # This file is autogenerated by the command `make fix-copies`, do not edit. | |
| from ..utils import DummyObject, requires_backends | |
| class FlaxStableDiffusionControlNetPipeline(metaclass=DummyObject): | |
| _backends = ["flax", "transformers"] | |
| def __init__(self, *args, **kwargs): | |
| requires_backends(self, ["flax", "transformers"]) | |
| def from_config(cls, *args, **kwargs): | |
| requires_backends(cls, ["flax", "transformers"]) | |
| def from_pretrained(cls, *args, **kwargs): | |
| requires_backends(cls, ["flax", "transformers"]) | |
| class FlaxStableDiffusionImg2ImgPipeline(metaclass=DummyObject): | |
| _backends = ["flax", "transformers"] | |
| def __init__(self, *args, **kwargs): | |
| requires_backends(self, ["flax", "transformers"]) | |
| def from_config(cls, *args, **kwargs): | |
| requires_backends(cls, ["flax", "transformers"]) | |
| def from_pretrained(cls, *args, **kwargs): | |
| requires_backends(cls, ["flax", "transformers"]) | |
| class FlaxStableDiffusionInpaintPipeline(metaclass=DummyObject): | |
| _backends = ["flax", "transformers"] | |
| def __init__(self, *args, **kwargs): | |
| requires_backends(self, ["flax", "transformers"]) | |
| def from_config(cls, *args, **kwargs): | |
| requires_backends(cls, ["flax", "transformers"]) | |
| def from_pretrained(cls, *args, **kwargs): | |
| requires_backends(cls, ["flax", "transformers"]) | |
| class FlaxStableDiffusionPipeline(metaclass=DummyObject): | |
| _backends = ["flax", "transformers"] | |
| def __init__(self, *args, **kwargs): | |
| requires_backends(self, ["flax", "transformers"]) | |
| def from_config(cls, *args, **kwargs): | |
| requires_backends(cls, ["flax", "transformers"]) | |
| def from_pretrained(cls, *args, **kwargs): | |
| requires_backends(cls, ["flax", "transformers"]) | |