Claude
725a5b0ff6
Changes: - README: Use 'examples' language instead of definitive model lists - Changed "models (SDXL, SD1.5, SD3)" to "including SDXL, SD1.5, SD3, and more" - Updated benchmarks to say "Example: SDXL-based model" - Renamed example workflows to be generic - Removed specific model size requirements - Remove redundant __version__ from __init__.py files - Version only tracked in pyproject.toml (single source of truth) - Fix y dimension detection for pooled embeddings - Improved detection to check label_emb layer dimensions - Added debug output to show detected y_dim - Should fix "mat1 and mat2 shapes cannot be multiplied (1x1280 and 2816x1280)" - Tries multiple detection methods before falling back to default Note: "Inserted 0 quantizers" issue still under investigation Version bumped to 0.1.4
28 lines
817 B
Python
28 lines
817 B
Python
"""
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ComfyUI NVIDIA ModelOpt Integration
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Custom nodes for quantizing and loading models optimized with NVIDIA ModelOpt.
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Installation:
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1. Place this folder in ComfyUI/custom_nodes/
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2. Install dependencies: pip install -r requirements.txt
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3. Restart ComfyUI
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For more information, see: https://github.com/EnragedAntelope/comfy-modelopt
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"""
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from .nodes import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
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__all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"]
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# Display startup message
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print("\n" + "="*60)
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print("NVIDIA ModelOpt for ComfyUI")
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print("="*60)
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print("Loaded nodes:")
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for node_name in NODE_CLASS_MAPPINGS.keys():
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print(f" • {node_name}")
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print("\nQuantize diffusion models with INT8, FP8, or INT4")
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print("Achieve ~2x faster inference with minimal quality loss")
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print("="*60 + "\n")
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