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
File size: 594 Bytes
8206b09 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import OptionalDependencyNotAvailable, 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 ShapEPipeline
else:
from .image_encoder import PaintByExampleImageEncoder
from .pipeline_paint_by_example import PaintByExamplePipeline
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