Instructions to use mhnakif/comfy2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mhnakif/comfy2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mhnakif/comfy2", 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: 781 Bytes
2795df7 | 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 | def merge_json_recursive(base, update):
"""Recursively merge two JSON-like objects.
- Dictionaries are merged recursively
- Lists are concatenated
- Other types are overwritten by the update value
Args:
base: Base JSON-like object
update: Update JSON-like object to merge into base
Returns:
Merged JSON-like object
"""
if not isinstance(base, dict) or not isinstance(update, dict):
if isinstance(base, list) and isinstance(update, list):
return base + update
return update
merged = base.copy()
for key, value in update.items():
if key in merged:
merged[key] = merge_json_recursive(merged[key], value)
else:
merged[key] = value
return merged
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