Upload folder using huggingface_hub

create-image-bf16.py

@@ -19,6 +19,7 @@ else:
     TRANSFORMER_FP8 = hf_hub_download(
         repo_id=MODEL_ID,
         filename="transformer/diffusion_pytorch_model.safetensors",
+        local_files_only=USE_LOCAL,
     )
     # TRANSFORMER_FP8 = hf_hub_download(repo_id=MODEL_ID, filename="transformer/diffusion_pytorch_model_e5m2.safetensors")
 
@@ -37,7 +38,7 @@ def load_fp8_transformer(fp8_path, config_root):
         config=config_root,
         subfolder="transformer",
         torch_dtype=torch.bfloat16,
-        local_files_only=True,
+        local_files_only=USE_LOCAL,
         low_cpu_mem_usage=False,
     )
 
@@ -50,7 +51,7 @@ pipe = ZImagePipeline.from_pretrained(
     local_files_only=USE_LOCAL,
     low_cpu_mem_usage=False,
 )
-pipe.transformer = load_fp8_transformer(TRANSFORMER_FP8, REPO_DIR)
+pipe.transformer = load_fp8_transformer(TRANSFORMER_FP8, MODEL_SRC)
 
 # [Optional] Attention Backend
 # Diffusers uses SDPA by default. Switch to Flash Attention for better efficiency if supported:

create-image.py

@@ -20,6 +20,7 @@ else:
     TRANSFORMER_FP8 = hf_hub_download(
         repo_id=MODEL_ID,
         filename="transformer/diffusion_pytorch_model.safetensors",
+        local_files_only=USE_LOCAL,
     )
     # TRANSFORMER_FP8 = hf_hub_download(repo_id=MODEL_ID, filename="transformer/diffusion_pytorch_model_e5m2.safetensors")
 
@@ -37,7 +38,7 @@ def load_fp8_transformer(fp8_path, config_root):
         config=config_root,
         subfolder="transformer",
         torch_dtype=torch.bfloat16,
-        local_files_only=True,
+        local_files_only=USE_LOCAL,
         low_cpu_mem_usage=False,
     )
 
@@ -71,7 +72,7 @@ pipe = ZImagePipeline.from_pretrained(
     local_files_only=USE_LOCAL,
     low_cpu_mem_usage=False,
 )
-pipe.transformer = load_fp8_transformer(TRANSFORMER_FP8, REPO_DIR)
+pipe.transformer = load_fp8_transformer(TRANSFORMER_FP8, MODEL_SRC)
 
 try:
     import transformer_engine.pytorch as te