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Basic Genmo Mochi video model support.
To use: "Load CLIP" node with t5xxl + type mochi "Load Diffusion Model" node with the mochi dit file. "Load VAE" with the mochi vae file. EmptyMochiLatentVideo node for the latent. euler + linear_quadratic in the KSampler node.
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@@ -10,6 +10,7 @@ import comfy.text_encoders.sa_t5
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import comfy.text_encoders.aura_t5
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import comfy.text_encoders.hydit
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import comfy.text_encoders.flux
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import comfy.text_encoders.genmo
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from . import supported_models_base
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from . import latent_formats
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@@ -670,7 +671,36 @@ class FluxSchnell(Flux):
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out = model_base.Flux(self, model_type=model_base.ModelType.FLOW, device=device)
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return out
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class GenmoMochi(supported_models_base.BASE):
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unet_config = {
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"image_model": "mochi_preview",
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}
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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]
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sampling_settings = {
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"multiplier": 1.0,
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"shift": 1.0,
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}
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unet_extra_config = {}
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latent_format = latent_formats.Mochi
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memory_usage_factor = 2.0 #TODO
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supported_inference_dtypes = [torch.float16, torch.bfloat16, torch.float32]
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vae_key_prefix = ["vae."]
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text_encoder_key_prefix = ["text_encoders."]
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def get_model(self, state_dict, prefix="", device=None):
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out = model_base.GenmoMochi(self, device=device)
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return out
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def clip_target(self, state_dict={}):
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pref = self.text_encoder_key_prefix[0]
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t5_detect = comfy.text_encoders.sd3_clip.t5_xxl_detect(state_dict, "{}t5xxl.transformer.".format(pref))
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return supported_models_base.ClipTarget(comfy.text_encoders.genmo.MochiT5Tokenizer, comfy.text_encoders.genmo.mochi_te(**t5_detect))
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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]
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models += [SVD_img2vid]
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