Instructions to use YiYiXu/diff-diff-mellon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YiYiXu/diff-diff-mellon with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("YiYiXu/diff-diff-mellon", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
File size: 921 Bytes
ea17a8d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | import logging
from mellon.NodeBase import NodeBase
# Configure logger
logger = logging.getLogger("mellon")
logger.setLevel(logging.DEBUG)
# Initialize components manager
# components = ComponentsManager()
from custom import components
class DiffDiffDenoise(NodeBase):
def __init__(self, node_id=None):
super().__init__(node_id)
from diffusers.modular_pipelines.node_utils import ModularNode
from diffusers.modular_pipelines import ModularPipelineMixin
diffdiff = ModularPipelineMixin.from_pretrained("YiYiXu/modular-diffdiff", trust_remote_code=True)
diffdiff.blocks.pop("text_encoder")
diffdiff.blocks.pop("decode")
diffdiff.blocks.pop("ip_adapter")
self._diffdiff_block = ModularNode(diffdiff)
self._diffdiff_block.setup(components=components)
def execute(self, **kwargs):
return self._diffdiff_block.execute(**kwargs)
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