Upload 4 files

app.py

@@ -98,7 +98,7 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css, delete_cache=(60,
                     with gr.Row():
                         seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0)
                         randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-                        gpu_duration = gr.Slider(label="GPU time duration (seconds)", minimum=5, maximum=240, value=59)
+                        gpu_duration = gr.Slider(label="GPU time duration (seconds)", minimum=5, maximum=240, value=20)
                     with gr.Row():
                         width = gr.Slider(label="Width", minimum=MIN_IMAGE_SIZE, maximum=MAX_IMAGE_SIZE, step=32, value=1024) # 832
                         height = gr.Slider(label="Height", minimum=MIN_IMAGE_SIZE, maximum=MAX_IMAGE_SIZE, step=32, value=1024) # 1216

dc.py

@@ -53,10 +53,13 @@ from diffusers import FluxPipeline
 # import urllib.parse
 import subprocess
 
-subprocess.run("rm -rf /data-nvme/zerogpu-offload/*", env={}, shell=True)
+IS_ZERO = True if os.getenv("SPACES_ZERO_GPU", None) else False
+if IS_ZERO:
+    subprocess.run("rm -rf /data-nvme/zerogpu-offload/*", env={}, shell=True)
+    torch.backends.cuda.matmul.allow_tf32 = True
 
 ImageFile.LOAD_TRUNCATED_IMAGES = True
-torch.backends.cuda.matmul.allow_tf32 = True
+
 # os.environ["PYTORCH_NO_CUDA_MEMORY_CACHING"] = "1"
 print(os.getenv("SPACES_ZERO_GPU"))
 

modutils.py

@@ -508,12 +508,18 @@ def get_t2i_model_info(repo_id: str):
     return gr.update(value=md)
 
 
+MAX_MODEL_INFO = 100
+
+
 def get_tupled_model_list(model_list):
     if not model_list: return []
     #return [(x, x) for x in model_list] # for skipping this function
     tupled_list = []
-    for repo_id in model_list:
-        api = HfApi()
+    api = HfApi()
+    for i, repo_id in enumerate(model_list):
+        if i > MAX_MODEL_INFO:
+            tupled_list.append((repo_id, repo_id))
+            continue
         try:
             if not api.repo_exists(repo_id): continue
             model = api.model_info(repo_id=repo_id, timeout=0.5)
@@ -521,7 +527,7 @@ def get_tupled_model_list(model_list):
             print(f"{repo_id}: {e}")
             tupled_list.append((repo_id, repo_id))
             continue
-        if model.private or model.gated: continue
+        if model.tags is None: continue
         tags = model.tags
         info = []
         if not 'diffusers' in tags: continue

requirements.txt

@@ -1,8 +1,6 @@
 stablepy==0.6.1
 diffusers==0.31.0
 transformers==4.47.1
-#diffusers
-#transformers
 accelerate
 invisible_watermark
 datasets
@@ -11,6 +9,8 @@ numpy<2
 gdown
 opencv-python
 huggingface_hub
+hf_transfer
+hf_xet
 scikit-build-core
 https://github.com/abetlen/llama-cpp-python/releases/download/v0.3.4-cu124/llama_cpp_python-0.3.4-cp310-cp310-linux_x86_64.whl
 git+https://github.com/Maximilian-Winter/llama-cpp-agent
@@ -24,4 +24,5 @@ timm
 wrapt-timeout-decorator
 sentencepiece
 unidecode
-ultralytics>=8.3.47
+ultralytics>=8.3.47
+pydantic==2.10.6