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Support for Chroma - Flux1 Schnell distilled with CFG (#7355)

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* Upload files for Chroma Implementation

* Remove trailing whitespace

* trim more trailing whitespace..oops

* remove unused imports

* Add supported_inference_dtypes

* Set min_length to 0 and remove attention_mask=True

* Set min_length to 1

* get_mdulations added from blepping and minor changes

* Add lora conversion if statement in lora.py

* Update supported_models.py

* update model_base.py

* add uptream commits

* set modelType.FLOW, will cause beta scheduler to work properly

* Adjust memory usage factor and remove unnecessary code

* fix mistake

* reduce code duplication

* remove unused imports

* refactor for upstream sync

* sync chroma-support with upstream via syncbranch patch

* Update sd.py

* Add Chroma as option for the OptimalStepsScheduler node
This commit is contained in:
Silver
2025-05-01 02:57:00 +02:00
committed by GitHub
parent 39c27a3705
commit 4ca3d84277
11 changed files with 667 additions and 4 deletions
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comfy/lora.py
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@@ -252,7 +252,7 @@ def model_lora_keys_unet(model, key_map={}):
key_lora = k[len("diffusion_model."):-len(".weight")]
key_map["base_model.model.{}".format(key_lora)] = k #official hunyuan lora format
if isinstance(model, comfy.model_base.Flux): #Diffusers lora Flux
if isinstance(model, comfy.model_base.Flux) or isinstance(model, comfy.model_base.Chroma): #Diffusers lora Flux or a diffusers lora Chroma
diffusers_keys = comfy.utils.flux_to_diffusers(model.model_config.unet_config, output_prefix="diffusion_model.")
for k in diffusers_keys:
if k.endswith(".weight"):