Upload google_gemma-3-27b-it_1.py with huggingface_hub

google_gemma-3-27b-it_1.py

@@ -11,11 +11,10 @@
 # ///
 
 try:
-    # Load model directly
-    from transformers import AutoProcessor, AutoModelForImageTextToText
+    # Use a pipeline as a high-level helper
+    from transformers import pipeline
     
-    processor = AutoProcessor.from_pretrained("google/gemma-3-27b-it")
-    model = AutoModelForImageTextToText.from_pretrained("google/gemma-3-27b-it")
+    pipe = pipeline("image-text-to-text", model="google/gemma-3-27b-it")
     messages = [
         {
             "role": "user",
@@ -25,16 +24,7 @@ try:
             ]
         },
     ]
-    inputs = processor.apply_chat_template(
-    	messages,
-    	add_generation_prompt=True,
-    	tokenize=True,
-    	return_dict=True,
-    	return_tensors="pt",
-    ).to(model.device)
-    
-    outputs = model.generate(**inputs, max_new_tokens=40)
-    print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
+    pipe(text=messages)
     with open('google_gemma-3-27b-it_1.txt', 'w', encoding='utf-8') as f:
         f.write('Everything was good in google_gemma-3-27b-it_1.txt')
 except Exception as e:
@@ -48,13 +38,11 @@ except Exception as e:
 
     with open('google_gemma-3-27b-it_1.txt', 'a', encoding='utf-8') as f:
         import traceback
-        f.write('''
-```CODE: 
-# Load model directly
-from transformers import AutoProcessor, AutoModelForImageTextToText
+        f.write('''```CODE: 
+# Use a pipeline as a high-level helper
+from transformers import pipeline
 
-processor = AutoProcessor.from_pretrained("google/gemma-3-27b-it")
-model = AutoModelForImageTextToText.from_pretrained("google/gemma-3-27b-it")
+pipe = pipeline("image-text-to-text", model="google/gemma-3-27b-it")
 messages = [
     {
         "role": "user",
@@ -64,17 +52,9 @@ messages = [
         ]
     },
 ]
-inputs = processor.apply_chat_template(
-	messages,
-	add_generation_prompt=True,
-	tokenize=True,
-	return_dict=True,
-	return_tensors="pt",
-).to(model.device)
-
-outputs = model.generate(**inputs, max_new_tokens=40)
-print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
+pipe(text=messages)
 ```
+
 ERROR: 
 ''')
         traceback.print_exc(file=f)