New Diffusers structure

flux1-depth-dev_ComfyMerged.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:60411ac95079c2b3b037697bf55ab1d6c0bf82cd16bb4aae864bc5b8269229ec
+size 23803296696

InspectSafetensors.py → scripts/InspectSafetensors.py

@@ -205,16 +205,16 @@ if __name__ == "__main__":
     print("OPTION 1: Inspect your working checkpoint")
     print("-" * 80)
     inspect_checkpoint(
-        "test/Juggernaut-XL_v9_RunDiffusionPhoto_v2.safetensors",
+        "../flux1-depth-dev_ComfyMerged.safetensors",
         detailed=False  # Set to True for full key listing
     )
     
     print("\n\n")
     
     # Compare two checkpoints
-    print("OPTION 2: Compare working vs broken checkpoint")
-    print("-" * 80)
+    # print("OPTION 2: Compare working vs broken checkpoint")
+    # print("-" * 80)
     # compare_checkpoints(
-    #     "path/to/working_checkpoint.safetensors",
-    #     "path/to/broken_checkpoint.safetensors"
+    #     "Juggernaut-XL_v9_RunDiffusionPhoto_v2.safetensors",
+    #     "flux1-depth-dev_fp4_merged_model.safetensors"
     # )

MergeSafetensors2.py → scripts/MergeSafetensors2.py

@@ -147,10 +147,10 @@ def simple_merge_keep_structure(
 if __name__ == "__main__":
     # Option 1: Smart merge with key detection
     merge_for_comfyui(
-        unet_path="svdq-fp4_r32-flux.1-depth-dev.safetensors",
-        vae_path="vae/diffusion_pytorch_model.safetensors",
-        text_encoder_path="text_encoder/model.safetensors",
-        output_path="flux1-depth-dev_fp4_merged_model.safetensors",
+        unet_path="../flux1-depth-dev.safetensors",
+        vae_path="../vae/diffusion_pytorch_model.safetensors",
+        text_encoder_path="../text_encoder/model.safetensors",
+        output_path="../flux1-depth-dev_merged_model.safetensors",
         model_type="flux"
     )
     

scripts/MergeSafetensors3.py

@@ -0,0 +1,270 @@
+"""
+Convert Diffusers-format FLUX model to ComfyUI-compatible checkpoint.
+This handles the proper folder structure and key naming.
+"""
+
+from safetensors.torch import save_file, load_file
+import os
+import json
+from pathlib import Path
+
+def convert_diffusers_to_comfyui(
+    diffusers_folder,
+    output_path,
+    fp16=False
+):
+    """
+    Convert a Diffusers FLUX model folder to a single ComfyUI checkpoint.
+    
+    Args:
+        diffusers_folder: Path to folder containing model_index.json
+        output_path: Output path for the merged .safetensors file
+        fp16: If True, convert to float16 to save space
+    """
+    
+    diffusers_folder = Path(diffusers_folder)
+    
+    # Verify it's a Diffusers model
+    model_index = diffusers_folder / "model_index.json"
+    if not model_index.exists():
+        raise ValueError(f"Not a Diffusers model folder. Missing: {model_index}")
+    
+    with open(model_index) as f:
+        config = json.load(f)
+    
+    print("=" * 80)
+    print("DIFFUSERS TO COMFYUI CONVERTER")
+    print("=" * 80)
+    print(f"\nModel: {config.get('_name_or_path', 'Unknown')}")
+    print(f"Format: {config.get('_class_name', 'Unknown')}")
+    
+    merged_state = {}
+    
+    # ========================================================================
+    # 1. Load Transformer (main FLUX model)
+    # ========================================================================
+    print("\n" + "=" * 80)
+    print("Loading Transformer...")
+    print("=" * 80)
+    
+    transformer_path = diffusers_folder / "transformer"
+    transformer_file = None
+    
+    # Find the safetensors file
+    for file in transformer_path.glob("*.safetensors"):
+        transformer_file = file
+        break
+    
+    if not transformer_file:
+        raise ValueError(f"No safetensors file found in {transformer_path}")
+    
+    print(f"Found: {transformer_file.name}")
+    transformer_state = load_file(str(transformer_file))
+    print(f"Loaded {len(transformer_state)} transformer parameters")
+    
+    # Add transformer weights (keep original keys or minimal prefix)
+    for key, value in transformer_state.items():
+        if fp16 and value.dtype.is_floating_point:
+            value = value.half()
+        merged_state[key] = value
+    
+    # ========================================================================
+    # 2. Load VAE
+    # ========================================================================
+    print("\n" + "=" * 80)
+    print("Loading VAE...")
+    print("=" * 80)
+    
+    vae_path = diffusers_folder / "vae"
+    vae_file = None
+    
+    for file in vae_path.glob("*.safetensors"):
+        vae_file = file
+        break
+    
+    if not vae_file:
+        print("⚠️  No VAE file found, skipping...")
+    else:
+        print(f"Found: {vae_file.name}")
+        vae_state = load_file(str(vae_file))
+        print(f"Loaded {len(vae_state)} VAE parameters")
+        
+        # Add VAE weights with proper prefix
+        for key, value in vae_state.items():
+            if fp16 and value.dtype.is_floating_point:
+                value = value.half()
+            # Keep original Diffusers VAE key structure
+            merged_state[key] = value
+    
+    # ========================================================================
+    # 3. Load Text Encoders (CLIP + T5)
+    # ========================================================================
+    print("\n" + "=" * 80)
+    print("Loading Text Encoders...")
+    print("=" * 80)
+    
+    # CLIP (text_encoder)
+    clip_path = diffusers_folder / "text_encoder"
+    if clip_path.exists():
+        clip_file = None
+        for file in clip_path.glob("*.safetensors"):
+            clip_file = file
+            break
+        
+        if clip_file:
+            print(f"Found CLIP: {clip_file.name}")
+            clip_state = load_file(str(clip_file))
+            print(f"Loaded {len(clip_state)} CLIP parameters")
+            
+            for key, value in clip_state.items():
+                if fp16 and value.dtype.is_floating_point:
+                    value = value.half()
+                # Keep original structure
+                merged_state[key] = value
+        else:
+            print("⚠️  No CLIP file found")
+    
+    # T5 (text_encoder_2) - often the largest component
+    t5_path = diffusers_folder / "text_encoder_2"
+    if t5_path.exists():
+        t5_file = None
+        for file in t5_path.glob("*.safetensors"):
+            t5_file = file
+            break
+        
+        if t5_file:
+            print(f"Found T5: {t5_file.name}")
+            print("⚠️  Loading T5 (this may take a while, it's large)...")
+            t5_state = load_file(str(t5_file))
+            print(f"Loaded {len(t5_state)} T5 parameters")
+            
+            for key, value in t5_state.items():
+                if fp16 and value.dtype.is_floating_point:
+                    value = value.half()
+                merged_state[key] = value
+        else:
+            print("⚠️  No T5 file found")
+    
+    # ========================================================================
+    # Save merged checkpoint
+    # ========================================================================
+    print("\n" + "=" * 80)
+    print("Saving merged checkpoint...")
+    print("=" * 80)
+    
+    print(f"Total parameters: {len(merged_state):,}")
+    print(f"Output: {output_path}")
+    
+    save_file(merged_state, output_path)
+    
+    size_gb = os.path.getsize(output_path) / (1024**3)
+    print(f"\n✅ Conversion complete!")
+    print(f"File size: {size_gb:.2f} GB")
+    
+    # Show key structure
+    print("\n" + "=" * 80)
+    print("Key Structure in Merged File")
+    print("=" * 80)
+    
+    sample_keys = list(merged_state.keys())[:10]
+    print("\nFirst 10 keys:")
+    for key in sample_keys:
+        print(f"  {key}")
+    
+    return output_path
+
+
+def convert_with_working_template(
+    diffusers_folder,
+    working_checkpoint,
+    output_path,
+    replace_transformer_only=True
+):
+    """
+    Use a working checkpoint as template, replacing components from Diffusers model.
+    This ensures key naming matches what ComfyUI expects.
+    
+    Args:
+        diffusers_folder: Path to Diffusers model folder
+        working_checkpoint: Path to a working ComfyUI checkpoint
+        output_path: Output path for merged checkpoint
+        replace_transformer_only: If True, only replace transformer, keep VAE/encoders from template
+    """
+    
+    print("=" * 80)
+    print("TEMPLATE-BASED CONVERSION")
+    print("=" * 80)
+    
+    # Load working checkpoint as template
+    print("\nLoading template checkpoint...")
+    template_state = load_file(working_checkpoint)
+    print(f"Template has {len(template_state)} parameters")
+    
+    # Get key prefixes from template
+    template_keys = set(template_state.keys())
+    transformer_keys = {k for k in template_keys if 'transformer' in k or 'double_blocks' in k or 'single_blocks' in k}
+    vae_keys = {k for k in template_keys if 'vae' in k.lower() or 'first_stage' in k}
+    text_encoder_keys = {k for k in template_keys if 'text_encoder' in k or 'clip' in k.lower()}
+    
+    print(f"\nTemplate structure:")
+    print(f"  Transformer keys: {len(transformer_keys)}")
+    print(f"  VAE keys: {len(vae_keys)}")
+    print(f"  Text encoder keys: {len(text_encoder_keys)}")
+    
+    # Load transformer from Diffusers
+    diffusers_folder = Path(diffusers_folder)
+    transformer_path = diffusers_folder / "transformer"
+    
+    transformer_file = next(transformer_path.glob("*.safetensors"))
+    print(f"\nLoading new transformer from: {transformer_file.name}")
+    new_transformer = load_file(str(transformer_file))
+    
+    # Replace transformer weights
+    print("\nReplacing transformer weights...")
+    merged_state = dict(template_state)  # Copy template
+    
+    # Replace matching keys
+    replaced = 0
+    for key in transformer_keys:
+        if key in new_transformer:
+            merged_state[key] = new_transformer[key]
+            replaced += 1
+    
+    print(f"Replaced {replaced} transformer parameters")
+    
+    if not replace_transformer_only:
+        print("\n⚠️  Also replacing VAE and text encoders...")
+        # Load and replace VAE
+        vae_file = next((diffusers_folder / "vae").glob("*.safetensors"), None)
+        if vae_file:
+            vae_state = load_file(str(vae_file))
+            for key in vae_keys:
+                if key in vae_state:
+                    merged_state[key] = vae_state[key]
+        
+        # Similar for text encoders...
+    
+    # Save
+    print(f"\nSaving to {output_path}...")
+    save_file(merged_state, output_path)
+    
+    size_gb = os.path.getsize(output_path) / (1024**3)
+    print(f"✅ Done! File size: {size_gb:.2f} GB")
+
+
+# Example usage
+if __name__ == "__main__":
+    # Method 1: Direct conversion
+    # convert_diffusers_to_comfyui(
+    #     diffusers_folder="../",
+    #     output_path="flux1-depth-dev_ComfyMerged.safetensors",
+    #     fp16=True  # Set False to keep original precision
+    # )
+    
+    #Method 2: Use working checkpoint as template (RECOMMENDED)
+    convert_with_working_template(
+        diffusers_folder="../",
+        working_checkpoint="../quantized/svdq-fp4_r32-flux.1-depth-dev.safetensors",
+        output_path="svdq-fp4_r32-flux.1-depth-dev_ComfyMerged.safetensors",
+        replace_transformer_only=True
+    )

scripts/MergeSafetensors4.py

@@ -0,0 +1,368 @@
+"""
+Convert Diffusers-format FLUX model to ComfyUI-compatible checkpoint.
+This handles the proper folder structure and key naming.
+"""
+
+from safetensors.torch import save_file, load_file
+import os
+import json
+from pathlib import Path
+
+def check_diffusers_structure(diffusers_folder):
+    """
+    Check and display the structure of a Diffusers model folder.
+    """
+    diffusers_folder = Path(diffusers_folder)
+    
+    print("=" * 80)
+    print("CHECKING DIFFUSERS FOLDER STRUCTURE")
+    print("=" * 80)
+    print(f"\nFolder: {diffusers_folder}")
+    
+    if not diffusers_folder.exists():
+        print(f"❌ Folder does not exist!")
+        return False
+    
+    # Check for model_index.json
+    model_index = diffusers_folder / "model_index.json"
+    if not model_index.exists():
+        print(f"❌ Not a Diffusers model (missing model_index.json)")
+        return False
+    
+    print(f"✅ Found model_index.json")
+    
+    # List all subfolders and files
+    print("\nFolder contents:")
+    for item in sorted(diffusers_folder.iterdir()):
+        if item.is_dir():
+            print(f"  📁 {item.name}/")
+            # List files in subfolder
+            for file in sorted(item.iterdir())[:5]:  # Show first 5 files
+                size_mb = file.stat().st_size / (1024**2)
+                print(f"      - {file.name} ({size_mb:.1f} MB)")
+            file_count = len(list(item.iterdir()))
+            if file_count > 5:
+                print(f"      ... and {file_count - 5} more files")
+        else:
+            size_mb = item.stat().st_size / (1024**2)
+            print(f"  📄 {item.name} ({size_mb:.1f} MB)")
+    
+    # Check expected components
+    print("\n" + "=" * 80)
+    print("Component Check")
+    print("=" * 80)
+    
+    components = {
+        "transformer": "Main FLUX transformer model",
+        "vae": "VAE encoder/decoder",
+        "text_encoder": "CLIP text encoder",
+        "text_encoder_2": "T5 text encoder"
+    }
+    
+    for folder_name, description in components.items():
+        folder_path = diffusers_folder / folder_name
+        if folder_path.exists():
+            safetensors_files = list(folder_path.glob("*.safetensors"))
+            if safetensors_files:
+                print(f"✅ {folder_name}: {description}")
+                print(f"   Found: {safetensors_files[0].name}")
+            else:
+                print(f"⚠️  {folder_name}: folder exists but no .safetensors files")
+        else:
+            print(f"❌ {folder_name}: missing")
+    
+    return True
+
+
+def convert_diffusers_to_comfyui(
+    diffusers_folder,
+    output_path,
+    fp16=False
+):
+    """
+    Convert a Diffusers FLUX model folder to a single ComfyUI checkpoint.
+    
+    Args:
+        diffusers_folder: Path to folder containing model_index.json
+        output_path: Output path for the merged .safetensors file
+        fp16: If True, convert to float16 to save space
+    """
+    
+    diffusers_folder = Path(diffusers_folder)
+    
+    # Verify it's a Diffusers model
+    model_index = diffusers_folder / "model_index.json"
+    if not model_index.exists():
+        raise ValueError(f"Not a Diffusers model folder. Missing: {model_index}")
+    
+    with open(model_index) as f:
+        config = json.load(f)
+    
+    print("=" * 80)
+    print("DIFFUSERS TO COMFYUI CONVERTER")
+    print("=" * 80)
+    print(f"\nModel: {config.get('_name_or_path', 'Unknown')}")
+    print(f"Format: {config.get('_class_name', 'Unknown')}")
+    
+    merged_state = {}
+    
+    # ========================================================================
+    # 1. Load Transformer (main FLUX model)
+    # ========================================================================
+    print("\n" + "=" * 80)
+    print("Loading Transformer...")
+    print("=" * 80)
+    
+    transformer_path = diffusers_folder / "transformer"
+    transformer_file = None
+    
+    # Find the safetensors file
+    if not transformer_path.exists():
+        raise ValueError(f"Transformer folder not found: {transformer_path}")
+    
+    for file in transformer_path.glob("*.safetensors"):
+        transformer_file = file
+        break
+    
+    if not transformer_file:
+        print(f"\n❌ No safetensors file found in: {transformer_path}")
+        print("\nFiles in transformer folder:")
+        for file in transformer_path.iterdir():
+            print(f"  - {file.name}")
+        raise ValueError(f"No safetensors file found in {transformer_path}")
+    
+    print(f"Found: {transformer_file.name}")
+    transformer_state = load_file(str(transformer_file))
+    print(f"Loaded {len(transformer_state)} transformer parameters")
+    
+    # Add transformer weights (keep original keys or minimal prefix)
+    for key, value in transformer_state.items():
+        if fp16 and value.dtype.is_floating_point:
+            value = value.half()
+        merged_state[key] = value
+    
+    # ========================================================================
+    # 2. Load VAE
+    # ========================================================================
+    print("\n" + "=" * 80)
+    print("Loading VAE...")
+    print("=" * 80)
+    
+    vae_path = diffusers_folder / "vae"
+    vae_file = None
+    
+    for file in vae_path.glob("*.safetensors"):
+        vae_file = file
+        break
+    
+    if not vae_file:
+        print("⚠️  No VAE file found, skipping...")
+    else:
+        print(f"Found: {vae_file.name}")
+        vae_state = load_file(str(vae_file))
+        print(f"Loaded {len(vae_state)} VAE parameters")
+        
+        # Add VAE weights with proper prefix
+        for key, value in vae_state.items():
+            if fp16 and value.dtype.is_floating_point:
+                value = value.half()
+            # Keep original Diffusers VAE key structure
+            merged_state[key] = value
+    
+    # ========================================================================
+    # 3. Load Text Encoders (CLIP + T5)
+    # ========================================================================
+    print("\n" + "=" * 80)
+    print("Loading Text Encoders...")
+    print("=" * 80)
+    
+    # CLIP (text_encoder)
+    clip_path = diffusers_folder / "text_encoder"
+    if clip_path.exists():
+        clip_file = None
+        for file in clip_path.glob("*.safetensors"):
+            clip_file = file
+            break
+        
+        if clip_file:
+            print(f"Found CLIP: {clip_file.name}")
+            clip_state = load_file(str(clip_file))
+            print(f"Loaded {len(clip_state)} CLIP parameters")
+            
+            for key, value in clip_state.items():
+                if fp16 and value.dtype.is_floating_point:
+                    value = value.half()
+                # Keep original structure
+                merged_state[key] = value
+        else:
+            print("⚠️  No CLIP file found")
+    
+    # T5 (text_encoder_2) - often the largest component
+    t5_path = diffusers_folder / "text_encoder_2"
+    if t5_path.exists():
+        t5_file = None
+        for file in t5_path.glob("*.safetensors"):
+            t5_file = file
+            break
+        
+        if t5_file:
+            print(f"Found T5: {t5_file.name}")
+            print("⚠️  Loading T5 (this may take a while, it's large)...")
+            t5_state = load_file(str(t5_file))
+            print(f"Loaded {len(t5_state)} T5 parameters")
+            
+            for key, value in t5_state.items():
+                if fp16 and value.dtype.is_floating_point:
+                    value = value.half()
+                merged_state[key] = value
+        else:
+            print("⚠️  No T5 file found")
+    
+    # ========================================================================
+    # Save merged checkpoint
+    # ========================================================================
+    print("\n" + "=" * 80)
+    print("Saving merged checkpoint...")
+    print("=" * 80)
+    
+    print(f"Total parameters: {len(merged_state):,}")
+    print(f"Output: {output_path}")
+    
+    save_file(merged_state, output_path)
+    
+    size_gb = os.path.getsize(output_path) / (1024**3)
+    print(f"\n✅ Conversion complete!")
+    print(f"File size: {size_gb:.2f} GB")
+    
+    # Show key structure
+    print("\n" + "=" * 80)
+    print("Key Structure in Merged File")
+    print("=" * 80)
+    
+    sample_keys = list(merged_state.keys())[:10]
+    print("\nFirst 10 keys:")
+    for key in sample_keys:
+        print(f"  {key}")
+    
+    return output_path
+
+
+def convert_with_working_template(
+    diffusers_folder,
+    working_checkpoint,
+    output_path,
+    replace_transformer_only=True
+):
+    """
+    Use a working checkpoint as template, replacing components from Diffusers model.
+    This ensures key naming matches what ComfyUI expects.
+    
+    Args:
+        diffusers_folder: Path to Diffusers model folder
+        working_checkpoint: Path to a working ComfyUI checkpoint
+        output_path: Output path for merged checkpoint
+        replace_transformer_only: If True, only replace transformer, keep VAE/encoders from template
+    """
+    
+    print("=" * 80)
+    print("TEMPLATE-BASED CONVERSION")
+    print("=" * 80)
+    
+    # Load working checkpoint as template
+    print("\nLoading template checkpoint...")
+    template_state = load_file(working_checkpoint)
+    print(f"Template has {len(template_state)} parameters")
+    
+    # Get key prefixes from template
+    template_keys = set(template_state.keys())
+    transformer_keys = {k for k in template_keys if 'transformer' in k or 'double_blocks' in k or 'single_blocks' in k}
+    vae_keys = {k for k in template_keys if 'vae' in k.lower() or 'first_stage' in k}
+    text_encoder_keys = {k for k in template_keys if 'text_encoder' in k or 'clip' in k.lower()}
+    
+    print(f"\nTemplate structure:")
+    print(f"  Transformer keys: {len(transformer_keys)}")
+    print(f"  VAE keys: {len(vae_keys)}")
+    print(f"  Text encoder keys: {len(text_encoder_keys)}")
+    
+    # Load transformer from Diffusers
+    diffusers_folder = Path(diffusers_folder)
+    transformer_path = diffusers_folder / "transformer"
+    
+    if not transformer_path.exists():
+        raise ValueError(f"Transformer folder not found: {transformer_path}")
+    
+    # Find safetensors file (try multiple patterns)
+    transformer_file = None
+    patterns = ["*.safetensors", "model.safetensors", "diffusion_pytorch_model.safetensors"]
+    
+    for pattern in patterns:
+        files = list(transformer_path.glob(pattern))
+        if files:
+            transformer_file = files[0]
+            break
+    
+    # If still not found, list what's actually there
+    if not transformer_file:
+        print(f"\n❌ No safetensors file found in: {transformer_path}")
+        print("\nFiles in transformer folder:")
+        for file in transformer_path.iterdir():
+            print(f"  - {file.name}")
+        raise ValueError("Could not find transformer safetensors file. See list above.")
+    
+    print(f"\nLoading new transformer from: {transformer_file.name}")
+    new_transformer = load_file(str(transformer_file))
+    
+    # Replace transformer weights
+    print("\nReplacing transformer weights...")
+    merged_state = dict(template_state)  # Copy template
+    
+    # Replace matching keys
+    replaced = 0
+    for key in transformer_keys:
+        if key in new_transformer:
+            merged_state[key] = new_transformer[key]
+            replaced += 1
+    
+    print(f"Replaced {replaced} transformer parameters")
+    
+    if not replace_transformer_only:
+        print("\n⚠️  Also replacing VAE and text encoders...")
+        # Load and replace VAE
+        vae_file = next((diffusers_folder / "vae").glob("*.safetensors"), None)
+        if vae_file:
+            vae_state = load_file(str(vae_file))
+            for key in vae_keys:
+                if key in vae_state:
+                    merged_state[key] = vae_state[key]
+        
+        # Similar for text encoders...
+    
+    # Save
+    print(f"\nSaving to {output_path}...")
+    save_file(merged_state, output_path)
+    
+    size_gb = os.path.getsize(output_path) / (1024**3)
+    print(f"✅ Done! File size: {size_gb:.2f} GB")
+
+
+# Example usage
+if __name__ == "__main__":
+    # Step 0: Check folder structure first
+    check_diffusers_structure("../")
+    
+    print("\n\n")
+    
+    # Method 1: Direct conversion
+    # convert_diffusers_to_comfyui(
+    #     diffusers_folder="../",
+    #     output_path="flux1-depth-dev_ComfyMerged.safetensors",
+    #     fp16=True  # Set False to keep original precision
+    # )
+    
+    #Method 2: Use working checkpoint as template (RECOMMENDED)
+    convert_with_working_template(
+        diffusers_folder="../",
+        working_checkpoint="../flux1-depth-dev.safetensors",
+        output_path="../flux1-depth-dev_ComfyMerged.safetensors",
+        replace_transformer_only=False
+    )

text_encoder_2/config.json

@@ -0,0 +1,32 @@
+{
+  "_name_or_path": "google/t5-v1_1-xxl",
+  "architectures": [
+    "T5EncoderModel"
+  ],
+  "classifier_dropout": 0.0,
+  "d_ff": 10240,
+  "d_kv": 64,
+  "d_model": 4096,
+  "decoder_start_token_id": 0,
+  "dense_act_fn": "gelu_new",
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "gated-gelu",
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "is_gated_act": true,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "t5",
+  "num_decoder_layers": 24,
+  "num_heads": 64,
+  "num_layers": 24,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.46.2",
+  "use_cache": true,
+  "vocab_size": 32128
+}

flux1-depth-dev_fp4_merged_model.safetensors → text_encoder_2/model-00001-of-00004.safetensors

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+size 4989319680

text_encoder_2/model-00002-of-00004.safetensors

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+size 4999830656

text_encoder_2/model-00003-of-00004.safetensors

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+size 4865612720

text_encoder_2/model-00004-of-00004.safetensors

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