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Merge branch 'comfyanonymous:master' into master

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patientx 2024-11-26 11:50:33 +03:00 committed by GitHub
commit 9fe09c02c2
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2 changed files with 21 additions and 1 deletions
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11
comfy/lora.py
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@ -62,6 +62,7 @@ def load_lora(lora, to_load):
diffusers_lora = "{}_lora.up.weight".format(x)
diffusers2_lora = "{}.lora_B.weight".format(x)
diffusers3_lora = "{}.lora.up.weight".format(x)
mochi_lora = "{}.lora_B".format(x)
transformers_lora = "{}.lora_linear_layer.up.weight".format(x)
A_name = None
@ -81,6 +82,10 @@ def load_lora(lora, to_load):
A_name = diffusers3_lora
B_name = "{}.lora.down.weight".format(x)
mid_name = None
elif mochi_lora in lora.keys():
A_name = mochi_lora
B_name = "{}.lora_A".format(x)
mid_name = None
elif transformers_lora in lora.keys():
A_name = transformers_lora
B_name ="{}.lora_linear_layer.down.weight".format(x)
@ -362,6 +367,12 @@ def model_lora_keys_unet(model, key_map={}):
key_map["lycoris_{}".format(k[:-len(".weight")].replace(".", "_"))] = to #simpletrainer lycoris
key_map["lora_transformer_{}".format(k[:-len(".weight")].replace(".", "_"))] = to #onetrainer
if isinstance(model, comfy.model_base.GenmoMochi):
for k in sdk:
if k.startswith("diffusion_model.") and k.endswith(".weight"): #Official Mochi lora format
key_lora = k[len("diffusion_model."):-len(".weight")]
key_map["{}".format(key_lora)] = k
return key_map

11
comfy/supported_models.py
View File

@ -659,6 +659,15 @@ class Flux(supported_models_base.BASE):
t5_detect = comfy.text_encoders.sd3_clip.t5_xxl_detect(state_dict, "{}t5xxl.transformer.".format(pref))
return supported_models_base.ClipTarget(comfy.text_encoders.flux.FluxTokenizer, comfy.text_encoders.flux.flux_clip(**t5_detect))
class FluxInpaint(Flux):
unet_config = {
"image_model": "flux",
"guidance_embed": True,
"in_channels": 96,
}
supported_inference_dtypes = [torch.bfloat16, torch.float32]
class FluxSchnell(Flux):
unet_config = {
"image_model": "flux",
@ -731,6 +740,6 @@ class LTXV(supported_models_base.BASE):
t5_detect = comfy.text_encoders.sd3_clip.t5_xxl_detect(state_dict, "{}t5xxl.transformer.".format(pref))
return supported_models_base.ClipTarget(comfy.text_encoders.lt.LTXVT5Tokenizer, comfy.text_encoders.lt.ltxv_te(**t5_detect))
models = [Stable_Zero123, SD15_instructpix2pix, SD15, SD20, SD21UnclipL, SD21UnclipH, SDXL_instructpix2pix, SDXLRefiner, SDXL, SSD1B, KOALA_700M, KOALA_1B, Segmind_Vega, SD_X4Upscaler, Stable_Cascade_C, Stable_Cascade_B, SV3D_u, SV3D_p, SD3, StableAudio, AuraFlow, HunyuanDiT, HunyuanDiT1, Flux, FluxSchnell, GenmoMochi, LTXV]
models = [Stable_Zero123, SD15_instructpix2pix, SD15, SD20, SD21UnclipL, SD21UnclipH, SDXL_instructpix2pix, SDXLRefiner, SDXL, SSD1B, KOALA_700M, KOALA_1B, Segmind_Vega, SD_X4Upscaler, Stable_Cascade_C, Stable_Cascade_B, SV3D_u, SV3D_p, SD3, StableAudio, AuraFlow, HunyuanDiT, HunyuanDiT1, FluxInpaint, Flux, FluxSchnell, GenmoMochi, LTXV]
models += [SVD_img2vid]