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Updated example workflows, added additional experimental workflows, added coverage for LTX loader

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John Pollock
2024-12-23 15:39:23 -06:00
parent 56e2e61e52
commit 19c0abd5ec
9 changed files with 7609 additions and 713 deletions
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README.md
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@@ -50,13 +50,43 @@ This workflow loads two SDXL checkpoints on two different GPUs. The first checkp
- [Download](examples/flux1dev_2gpu.json)
This workflow loads a FLUX.1-dev model and splits it across two GPUs. The UNet model is loaded on GPU 0 while the text encoders and VAE are loaded on GPU 1.
This workflow loads a FLUX.1-dev model and splits it across two GPUs. The UNet model is loaded on GPU 1 while the text encoders and VAE are loaded on GPU 0.
### FLUX.1-dev and SDXL in the same workflow
- [Download](examples/flux1dev_sdxl_2gpu.json)
This workflow loads a FLUX.1-dev model and an SDXL model in the same workflow. The FLUX.1-dev model is loaded on GPU 0, and the SDXL model is loaded on GPU 1.
This workflow loads a FLUX.1-dev model and an SDXL model in the same workflow. The FLUX.1-dev model has its UNet on GPU 1 with VAE and text encoders on GPU 0, while the SDXL model uses separate allocations.
### Using GGUF quantized models across GPUs
- [Download](examples/flux1dev_2gpu_GGUF.json)
This workflow demonstrates using quantized GGUF models split across multiple GPUs for reduced VRAM usage with the UNet on GPU 1, VAE and text encoders on GPU 0.
### EXPERIMENTAL - USE AT YOUR OWN RISK
These workflows combine multiple features and non-core loaders types and may require significant VRAM to execute. They are provided as examples of what's possible but may require adjustment for your specific setup.
#### Multi-Model Video Generation Pipeline
- [Download](examples/florence2_flux1dev_ltxv_2gpu_GGUF.json)
This workflow creates an img2txt2img2vid video generation pipeline by:
1. Taking a starting image for analysis by Florence2
2. Using the Florence2 data for a FLUX.1 Dev image prompt
3. Taking the FLUX.1 image prompt and providing it as the starting image for LTX Video
4. Generate a 5 second video based on the provided image
All models are distributed across available GPUs with no reloading on dual 3090s
#### LLM-Guided Video Generation
- [Download](examples/llamacpp_ltxv_2gpu_GGUF.json)
This workflow demonstrates:
1. Using a local LLM (loaded on first GPU via llama.cpp) to take a text suggestion and craft an LTX Video promot
2. Feeding the enhanced prompt to LTXVideo (loaded on second GPU) for video generation
Requires appropriate LLM and LTXVideo models.
## Support
__init__.py
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@@ -38,9 +38,11 @@ time.sleep(2) # This is to make sure the other nodes are already loaded
from nodes import NODE_CLASS_MAPPINGS as GLOBAL_NODE_CLASS_MAPPINGS
TARGET_NODE_NAMES = {
"UNETLoader", "VAELoader", "CLIPLoader", "DualCLIPLoader", "TripleCLIPLoader", "CheckpointLoaderSimple", "ControlNetLoader",
"UnetLoaderGGUF", "UnetLoaderGGUFAdvanced", "CLIPLoaderGGUF", "DualCLIPLoaderGGUF", "TripleCLIPLoaderGGUF",
"LoadFluxControlNet",
"UNETLoader", "VAELoader", "CLIPLoader", "DualCLIPLoader", "TripleCLIPLoader", "CheckpointLoaderSimple", "ControlNetLoader", # ComfyUI Core Nodes - https://github.com/comfyanonymous/ComfyUI
"UnetLoaderGGUF", "UnetLoaderGGUFAdvanced", "CLIPLoaderGGUF", "DualCLIPLoaderGGUF", "TripleCLIPLoaderGGUF", # ComfyUI-GGUF - https://github.com/city96/ComfyUI-GGUF
"LoadFluxControlNet", # x-flux-comfyui - https://github.com/XLabs-AI/x-flux-comfyui
"Florence2ModelLoader", "DownloadAndLoadFlorence2Model", # ComfyUI-Florence2 - https://github.com/kijai/ComfyUI-Florence2
"LTXVLoader", # ComfyUI-LTXVideo - https://github.com/Lightricks/ComfyUI-LTXVideo
}
NODE_CLASS_MAPPINGS = {}
examples/florence2_flux1dev_ltxv_2gpu_GGUF.json
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examples/flux1dev_2gpu.json
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examples/flux1dev_2gpu_GGUF.json
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