Update app.py

app.py

@@ -9,9 +9,11 @@ model_cache = {}
 
 # Available models
 AVAILABLE_MODELS = {
-    "Apollo-1-4B": "NoemaResearch/Apollo-1-4B",
-    "Apollo-1-8B": "NoemaResearch/Apollo-1-8B",
-    "Apollo-1-2B": "NoemaResearch/Apollo-1-2B",
+    "Apollo-1-4B": "Loom-Labs/Apollo-1-4B",
+    "Apollo-1-8B": "Loom-Labs/Apollo-1-8B",
+    "Apollo-1-2B": "Loom-Labs/Apollo-1-2B",
+    "Daedalus-1-2B": "Loom-Labs/Daedalus-1-2B",
+    "Daedalus-1-8B": "Loom-Labs/Daedalus-1-8B",
 }
 
 @spaces.GPU
@@ -188,14 +190,16 @@ def generate(
 def create_interface():
     with gr.Blocks(title="Multi-Model Chat") as demo:
         gr.Markdown("""
-        # 🚀 Apollo-1 Model Chat Interface
+        # 🚀 Loom Labs Model Chat Interface
         
-        Chat with the Apollo-1 models by Noema Research.
+        Chat with the models by Loom Labs.
         
         **Available Models:**
         - Apollo-1-4B (4 billion parameters)
         - Apollo-1-8B (8 billion parameters)
         - Apollo-1-2B (2 billion parameters)
+        - Daedalus-1-2B (2 billion parameters)
+        - Daedalus-1-8B (8 billion parameters)
         """)
         
         with gr.Row():
@@ -282,20 +286,6 @@ def create_interface():
         
         model_selector.change(model_changed, model_selector, chatbot)
         
-        gr.Markdown("""
-        ---
-        
-        ### About the Apollo-1 Models
-        **Apollo-1-2B**: 2 billion parameter model by Noema Research, designed for fast and quick infrencing
-        
-        **Apollo-1-4B**: 4 billion parameter model by Noema Research, optimisd for efficient conversation and text generation
-        
-        **Apollo-1-8B**: 8 billion parameter model by Noema Research, offering enhanced capabilities and better performance for complex tasks
-        
-        All models are designed for conversational AI and support various text generation tasks. The 8B model provides more sophisticated responses but requires more computational resources.
-        
-        This Space uses ZeroGPU for efficient GPU allocation across both model sizes.
-        """)
     
     return demo