Update app.py

app.py

@@ -209,19 +209,18 @@ def quantize(model_path, repo_id, quant_method=None):
 
 def create_readme(repo_name, base_model_name, lora_model_name, quant_methods):
     readme_path = os.path.join("output", repo_name, "README.md")
-    readme_template = f"""
----
+    readme_template = """---
 tags:
 - autotrain
 - text-generation-inference
 - text-generation
-- peft{"\n- quantization" if len(quant_methods) > 0 else ""}
+- peft{quantization}
 library_name: transformers
 base_model: {base_model_name}
 widget:
 - messages:
     - role: user
-        content: What is your favorite condiment?
+      content: What is your favorite condiment?
 license: other
 datasets:
 - {lora_model_name}
@@ -231,8 +230,16 @@ datasets:
 base_model: {base_model_name}
 lora_model: {lora_model_name}
 quant_methods: {quant_methods}
-created_at: {time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())}
-created_by: [Steven10429/apply_lora_and_quantize](https://github.com/Steven10429/apply_lora_and_quantize)"""
+created_at: {created_at}
+created_by: [Steven10429/apply_lora_and_quantize](https://github.com/Steven10429/apply_lora_and_quantize)
+""".format(
+        quantization="\n- quantization" if len(quant_methods) > 0 else "",
+        base_model_name=base_model_name,
+        lora_model_name=lora_model_name,
+        repo_name=repo_name,
+        quant_methods=quant_methods,
+        created_at=time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
+    )
     
     with open(readme_path, "w") as f:
         f.write(readme_template)
@@ -284,9 +291,11 @@ def process_model(base_model_name, lora_model_name, repo_name, quant_methods, hf
             num_workers=os.cpu_count() if os.cpu_count() > 4 else 4,
             print_report_every=10,
         )
+        log("Upload completed.")
         
         # rm -rf model_path
         shutil.rmtree(model_path)
+        log("Removed model from local")
         
         return "\n".join(current_logs)
     except Exception as e: