switch to deepseek 8B

app.py

@@ -68,12 +68,7 @@ def preprocess_image(image: Image.Image) -> Image.Image:
     if trellis is None:
         # If the pipeline is not loaded, just return the original image
         return image
-    
-    # Check if image is a numpy array and convert to PIL Image if needed
-    if isinstance(image, np.ndarray):
-        image = Image.fromarray(image.astype('uint8'))
         
-    # trellis.cuda()
     processed_image = trellis.preprocess_image(image)
     return processed_image
 
@@ -104,8 +99,8 @@ def get_text_gen_pipeline():
         try:
             device = "cuda" if torch.cuda.is_available() else "cpu"
             tokenizer = AutoTokenizer.from_pretrained(
-                # "mistralai/Mistral-7B-Instruct-v0.3",
-                "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
+                "mistralai/Mistral-7B-Instruct-v0.3",
+                "deepseek-ai/DeepSeek-R1-Distill-Llama-8B",
                 use_fast=True
             )
             tokenizer.pad_token = tokenizer.pad_token or tokenizer.eos_token
@@ -113,7 +108,7 @@ def get_text_gen_pipeline():
             _text_gen_pipeline = pipeline(
                 # "text-generation",
                 # model="mistralai/Mistral-7B-Instruct-v0.3",
-                model="deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
+                model="deepseek-ai/DeepSeek-R1-Distill-Llama-8B",
                 tokenizer=tokenizer,
                 max_new_tokens=2048,
                 device=device,
@@ -138,7 +133,11 @@ def get_trellis_pipeline():
 
 
 @spaces.GPU()
-def refine_prompt(prompt, system_prompt=DEFAULT_SYSTEM_PROMPT, progress=gr.Progress()):
+def refine_prompt(
+        prompt, 
+        system_prompt=DEFAULT_SYSTEM_PROMPT, 
+        progress=gr.Progress(track_tqdm=True)
+        ): 
     text_gen = get_text_gen_pipeline()
     if text_gen is None:
         return "", "Text generation model is unavailable."