Update model_card_template.md

model_card_template.md

@@ -5,7 +5,7 @@ tags:
 - onnx
 ---
 
-# AMOP-Optimized CPU Model: {repo_name}
+# AMOP-Optimized ONNX Model: {repo_name}
 
 This model was automatically optimized for CPU inference using the **Adaptive Model Optimization Pipeline (AMOP)**.
 
@@ -14,13 +14,9 @@ This model was automatically optimized for CPU inference using the **Adaptive Mo
 
 ## Optimization Details
 
-The following AMOP stages were applied:
-- **Stage 2: Pruning:** {pruning_status} (Percentage: {pruning_percent}%)
-- **Stage 3 & 4: Quantization & ONNX Conversion:** Enabled (Dynamic Quantization)
-
-## Performance Metrics
-
-{eval_report}
+The following AMOP ONNX pipeline stages were applied:
+- **Pruning:** {pruning_status} (Percentage: {pruning_percent}%)
+- **Quantization & ONNX Conversion:** Enabled ({quant_type} Quantization)
 
 ## How to Use
 
@@ -40,5 +36,10 @@ gen_tokens = model.generate(**inputs)
 print(tokenizer.batch_decode(gen_tokens))
 ```
 ## AMOP Pipeline Log
+<details>
+<summary>Click to expand</summary>
 
+```
 {pipeline_log}
+```
+</details>