Single and dual clip loader nodes support SD3.

You can use the CLIPLoader to use the t5xxl only or the DualCLIPLoader to
use CLIP-L and CLIP-G only for sd3.

comfy/sd.py

@@ -370,6 +370,7 @@ def load_style_model(ckpt_path):
 class CLIPType(Enum):
     STABLE_DIFFUSION = 1
     STABLE_CASCADE = 2
+    SD3 = 3
 
 def load_clip(ckpt_paths, embedding_directory=None, clip_type=CLIPType.STABLE_DIFFUSION):
     clip_data = []
@@ -399,12 +400,20 @@ def load_clip(ckpt_paths, embedding_directory=None, clip_type=CLIPType.STABLE_DI
         elif "text_model.encoder.layers.22.mlp.fc1.weight" in clip_data[0]:
             clip_target.clip = sd2_clip.SD2ClipModel
             clip_target.tokenizer = sd2_clip.SD2Tokenizer
+        elif "encoder.block.23.layer.1.DenseReluDense.wi_1.weight" in clip_data[0]:
+            dtype_t5 = clip_data[0]["encoder.block.23.layer.1.DenseReluDense.wi_1.weight"].dtype
+            clip_target.clip = sd3_clip.sd3_clip(clip_l=False, clip_g=False, t5=True, dtype_t5=dtype_t5)
+            clip_target.tokenizer = sd3_clip.SD3Tokenizer
         else:
             clip_target.clip = sd1_clip.SD1ClipModel
             clip_target.tokenizer = sd1_clip.SD1Tokenizer
     elif len(clip_data) == 2:
-        clip_target.clip = sdxl_clip.SDXLClipModel
-        clip_target.tokenizer = sdxl_clip.SDXLTokenizer
+        if clip_type == CLIPType.SD3:
+            clip_target.clip = sd3_clip.sd3_clip(clip_l=True, clip_g=True, t5=False)
+            clip_target.tokenizer = sd3_clip.SD3Tokenizer
+        else:
+            clip_target.clip = sdxl_clip.SDXLClipModel
+            clip_target.tokenizer = sdxl_clip.SDXLTokenizer
     elif len(clip_data) == 3:
         clip_target.clip = sd3_clip.SD3ClipModel
         clip_target.tokenizer = sd3_clip.SD3Tokenizer

comfy/sd3_clip.py

@@ -142,3 +142,9 @@ class SD3ClipModel(torch.nn.Module):
             return self.clip_l.load_sd(sd)
         else:
             return self.t5xxl.load_sd(sd)
+
+def sd3_clip(clip_l=True, clip_g=True, t5=True, dtype_t5=None):
+    class SD3ClipModel_(SD3ClipModel):
+        def __init__(self, device="cpu", dtype=None):
+            super().__init__(clip_l=clip_l, clip_g=clip_g, t5=t5, dtype_t5=dtype_t5, device=device, dtype=dtype)
+    return SD3ClipModel_

comfy/supported_models.py

@@ -522,11 +522,7 @@ class SD3(supported_models_base.BASE):
             t5 = True
             dtype_t5 = state_dict[t5_key].dtype
 
-        class SD3ClipModel(sd3_clip.SD3ClipModel):
-            def __init__(self, device="cpu", dtype=None):
-                super().__init__(clip_l=clip_l, clip_g=clip_g, t5=t5, dtype_t5=dtype_t5, device=device, dtype=dtype)
-
-        return supported_models_base.ClipTarget(sd3_clip.SD3Tokenizer, SD3ClipModel)
+        return supported_models_base.ClipTarget(sd3_clip.SD3Tokenizer, sd3_clip.sd3_clip(clip_l=clip_l, clip_g=clip_g, t5=t5, dtype_t5=dtype_t5))
 
 
 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]

nodes.py

@@ -818,7 +818,7 @@ class CLIPLoader:
     @classmethod
     def INPUT_TYPES(s):
         return {"required": { "clip_name": (folder_paths.get_filename_list("clip"), ),
-                              "type": (["stable_diffusion", "stable_cascade"], ),
+                              "type": (["stable_diffusion", "stable_cascade", "sd3"], ),
                              }}
     RETURN_TYPES = ("CLIP",)
     FUNCTION = "load_clip"
@@ -829,6 +829,8 @@ class CLIPLoader:
         clip_type = comfy.sd.CLIPType.STABLE_DIFFUSION
         if type == "stable_cascade":
             clip_type = comfy.sd.CLIPType.STABLE_CASCADE
+        elif type == "sd3":
+            clip_type = comfy.sd.CLIPType.SD3
 
         clip_path = folder_paths.get_full_path("clip", clip_name)
         clip = comfy.sd.load_clip(ckpt_paths=[clip_path], embedding_directory=folder_paths.get_folder_paths("embeddings"), clip_type=clip_type)
@@ -837,17 +839,24 @@ class CLIPLoader:
 class DualCLIPLoader:
     @classmethod
     def INPUT_TYPES(s):
-        return {"required": { "clip_name1": (folder_paths.get_filename_list("clip"), ), "clip_name2": (folder_paths.get_filename_list("clip"), ),
+        return {"required": { "clip_name1": (folder_paths.get_filename_list("clip"), ),
+                              "clip_name2": (folder_paths.get_filename_list("clip"), ),
+                              "type": (["sdxl", "sd3"], ),
                              }}
     RETURN_TYPES = ("CLIP",)
     FUNCTION = "load_clip"
 
     CATEGORY = "advanced/loaders"
 
-    def load_clip(self, clip_name1, clip_name2):
+    def load_clip(self, clip_name1, clip_name2, type):
         clip_path1 = folder_paths.get_full_path("clip", clip_name1)
         clip_path2 = folder_paths.get_full_path("clip", clip_name2)
-        clip = comfy.sd.load_clip(ckpt_paths=[clip_path1, clip_path2], embedding_directory=folder_paths.get_folder_paths("embeddings"))
+        if type == "sdxl":
+            clip_type = comfy.sd.CLIPType.STABLE_DIFFUSION
+        elif type == "sd3":
+            clip_type = comfy.sd.CLIPType.SD3
+
+        clip = comfy.sd.load_clip(ckpt_paths=[clip_path1, clip_path2], embedding_directory=folder_paths.get_folder_paths("embeddings"), clip_type=clip_type)
         return (clip,)
 
 class CLIPVisionLoader: