Upload app.py

app.py

@@ -49,7 +49,6 @@ def setup(
         return None, None, description
 
     try:
-        # Load the model and tokenizer
         model = AutoModelForCausalLM.from_pretrained(
             model_id, 
             torch_dtype=torch.bfloat16, 
@@ -73,6 +72,20 @@ def setup(
         
         return None, None, description
 
+DESCRIPTION = """\
+# Pearl-7B-0211-ties, an xtraordinary 7B model
+
+This space showcases the <a style='color:white;' href='https://huggingface.co/louisbrulenaudet/Pearl-7B-0211-ties'>Pearl-7B-0211-ties</a> 
+model by Louis Brulé Naudet, a language model with 7.24 billion parameters that achieves a score exceeding 75.10 on the Open LLM Leaderboard 
+(average).
+"""
+
+model, tokenizer, description = setup(
+    model_id="louisbrulenaudet/Pearl-7B-0211-ties", 
+    description=DESCRIPTION
+)
+
+print(model, tokenizer)
 
 def preprocess_conversation(
     message: str, 
@@ -264,20 +277,6 @@ def generate(
 
     return "".join(outputs)
 
-
-DESCRIPTION = """\
-# Pearl-7B-0211-ties, an xtraordinary 7B model
-
-This space showcases the <a style='color:white;' href='https://huggingface.co/louisbrulenaudet/Pearl-7B-0211-ties'>Pearl-7B-0211-ties</a> 
-model by Louis Brulé Naudet, a language model with 7.24 billion parameters that achieves a score exceeding 75.10 on the Open LLM Leaderboard 
-(average).
-"""
-
-model, tokenizer, description = setup(
-    model_id="louisbrulenaudet/Pearl-7B-0211-ties", 
-    description=DESCRIPTION
-)
-
 chat_interface = gr.ChatInterface(
     fn=generate,
     additional_inputs=[