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examples/cogvideox_Fun_180_orbit_01.json
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1922
examples/cogvideox_Fun_180_orbit_01.json
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@ -240,12 +240,7 @@ class DownloadAndLoadCogVideoModel:
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#LoRAs
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#LoRAs
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if lora is not None:
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if lora is not None:
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# from .lora_utils import merge_lora#, load_lora_into_transformer
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try:
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# if "fun" in model.lower():
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# for l in lora:
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# log.info(f"Merging LoRA weights from {l['path']} with strength {l['strength']}")
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# transformer = merge_lora(transformer, l["path"], l["strength"])
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#else:
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adapter_list = []
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adapter_list = []
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adapter_weights = []
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adapter_weights = []
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for l in lora:
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for l in lora:
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@ -271,6 +266,11 @@ class DownloadAndLoadCogVideoModel:
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if any(item in lora[-1]["path"].lower() for item in dimension_loras):
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if any(item in lora[-1]["path"].lower() for item in dimension_loras):
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lora_scale = lora_scale / lora_rank
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lora_scale = lora_scale / lora_rank
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pipe.fuse_lora(lora_scale=lora_scale, components=["transformer"])
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pipe.fuse_lora(lora_scale=lora_scale, components=["transformer"])
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except: #Fun trainer LoRAs are loaded differently
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from .lora_utils import merge_lora
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for l in lora:
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log.info(f"Merging LoRA weights from {l['path']} with strength {l['strength']}")
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transformer = merge_lora(transformer, l["path"], l["strength"])
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if "fused" in attention_mode:
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if "fused" in attention_mode:
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from diffusers.models.attention import Attention
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from diffusers.models.attention import Attention
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27
readme.md
27
readme.md
@ -1,5 +1,32 @@
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# WORK IN PROGRESS
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# WORK IN PROGRESS
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## BREAKING Update8
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This is big one, and unfortunately to do the necessary cleanup and refactoring this will break every old workflow as they are.
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I apologize for the inconvenience, if I don't do this now I'll keep making it worse until maintaining becomes too much of a chore, so from my pov there was no choice.
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*Please either use the new workflows or fix the nodes in your old ones before posting issue reports!*
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Old version will be kept in a legacy branch, but not maintained
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- Support CogVideoX 1.5 models
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- Major code cleanup (it was bad, still isn't great, wip)
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- Merge Fun -model functionality into main pipeline:
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- All Fun specific nodes, besides image encode node for Fun -InP models are gone
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- Main CogVideo Sampler works with Fun models
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- DimensionX LoRAs now work with Fun models as well
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- Remove width/height from the sampler widgets and detect from input instead, this meanst text2vid now requires using empty latents
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- Separate VAE from the model, allow using fp32 VAE
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- Add ability to load some of the non-GGUF models as single files (only few available for now: https://huggingface.co/Kijai/CogVideoX-comfy)
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- Add some torchao quantizations as options
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- Add interpolation as option for the main encode node, old interpolation specific node is gone
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- torch.compile optimizations
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- Remove PAB in favor of FasterCache and cleaner code
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- other smaller things I forgot about at this point
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For Fun -model based workflows it's more drastic change, for others migrating generally means re-setting many of the nodes.
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## Update7
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## Update7
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- Refactored the Fun version's sampler to accept any resolution, this should make it lot simpler to use with Tora. **BREAKS OLD WORKFLOWS**, old FunSampler nodes need to be remade.
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- Refactored the Fun version's sampler to accept any resolution, this should make it lot simpler to use with Tora. **BREAKS OLD WORKFLOWS**, old FunSampler nodes need to be remade.
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