switch to deepseek

app.py

@@ -92,9 +92,6 @@ def get_image_gen_pipeline():
                 torch_dtype=dtype,
             ).to(device)
             
-            # Comment these out for now to match the working example
-            # _image_gen_pipeline.enable_model_cpu_offload()
-            # _image_gen_pipeline.enable_vae_slicing()
         except Exception as e:
             print(f"Error loading image generation model: {e}")
             return None
@@ -107,14 +104,16 @@ 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",
+                # "mistralai/Mistral-7B-Instruct-v0.3",
+                "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
                 use_fast=True
             )
             tokenizer.pad_token = tokenizer.pad_token or tokenizer.eos_token
             
             _text_gen_pipeline = pipeline(
-                "text-generation",
-                model="mistralai/Mistral-7B-Instruct-v0.3",
+                # "text-generation",
+                # model="mistralai/Mistral-7B-Instruct-v0.3",
+                model="deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
                 tokenizer=tokenizer,
                 max_new_tokens=2048,
                 device=device,
@@ -375,7 +374,6 @@ def create_interface():
 
             gen3d_button = gr.Button("Create 3D visual with Trellis")
             video_output = gr.Video(label="Generated 3D Asset", autoplay=True, loop=True, height=300)
-            # model_output = LitModel3D(label="Extracted GLB/Gaussian", exposure=10.0, height=300)
             
             message_box = gr.Textbox(
                 label="Status Messages", 
@@ -432,9 +430,6 @@ def create_interface():
                         slat_guidance_strength = gr.Slider(0.0, 10.0, label="Guidance Strength", value=3.0, step=0.1)
                         slat_sampling_steps = gr.Slider(1, 50, label="Sampling Steps", value=12, step=1)
 
-
-            # output_buf = gr.State()
-
             gr.Examples(
                 examples=examples,
                 fn=process_example_pipeline,
@@ -463,36 +458,7 @@ def create_interface():
             inputs=[generated_image, trellis_seed, ss_guidance_strength, ss_sampling_steps, slat_guidance_strength, slat_sampling_steps],
             outputs=[output_state, video_output],
         )
-        # .then(
-        #     # Update button states after successful 3D generation
-        #     lambda: (gr.Button.update(interactive=True), gr.Button.update(interactive=True), "3D model generated successfully"),
-        #     outputs=[extract_glb_btn, extract_gs_btn, message_box]
-        # )
-        
-        # # Add handlers for GLB and Gaussian extraction
-        # gr.on(
-        #     triggers=[extract_glb_btn.click],
-        #     fn=extract_glb,
-        #     inputs=[output_state, mesh_simplify, texture_size],
-        #     outputs=[model_output, download_glb]
-        # ).then(
-        #     lambda path: (gr.DownloadButton.update(interactive=True, value=path), "GLB extraction completed"),
-        #     inputs=[model_output],
-        #     outputs=[download_glb, message_box]
-        # )
-
-        # gr.on(
-        #     triggers=[extract_gs_btn.click],
-        #     fn=extract_gaussian,
-        #     inputs=[output_state],
-        #     outputs=[model_output, download_gs]
-        # ).then(
-        #     lambda path: (gr.DownloadButton.update(interactive=True, value=path), "Gaussian extraction completed"),
-        #     inputs=[model_output],
-        #     outputs=[download_gs, message_box]
-        # )
-
-    # Don't put any demo.* method calls here outside the Blocks context
+
     return demo
 
 if __name__ == "__main__":