keep viewer

olmocr2-vllm.py

@@ -96,7 +96,7 @@ def parse_yaml_frontmatter(text: str) -> tuple[dict, str]:
         (metadata_dict, content_without_frontmatter)
     """
     # Match YAML front matter between --- markers
-    pattern = r'^---\s*\n(.*?)\n---\s*\n(.*)$'
+    pattern = r"^---\s*\n(.*?)\n---\s*\n(.*)$"
     match = re.match(pattern, text.strip(), re.DOTALL)
 
     if match:
@@ -179,7 +179,6 @@ def create_dataset_card(
     model_name = model.split("/")[-1]
 
     return f"""---
-viewer: false
 tags:
 - ocr
 - document-processing
@@ -315,6 +314,7 @@ def main(
         seed: Random seed for shuffling
     """
     import time
+
     start_time = time.time()
 
     # Check CUDA availability
@@ -396,7 +396,9 @@ def main(
 
             # Log warning if generation didn't finish naturally
             if finish_reason != "stop":
-                logger.warning(f"Generation did not finish naturally (reason: {finish_reason}), output may be incomplete")
+                logger.warning(
+                    f"Generation did not finish naturally (reason: {finish_reason}), output may be incomplete"
+                )
 
             metadata, content = parse_yaml_frontmatter(response_text)
             all_outputs.append(content)
@@ -405,25 +407,31 @@ def main(
     # Add results to dataset
     # Check if columns already exist and handle appropriately
     if output_column in ds.column_names:
-        logger.warning(f"Column '{output_column}' already exists, it will be overwritten")
+        logger.warning(
+            f"Column '{output_column}' already exists, it will be overwritten"
+        )
         ds = ds.remove_columns([output_column])
     ds = ds.add_column(output_column, all_outputs)
 
     if metadata_column_name in ds.column_names:
-        logger.warning(f"Column '{metadata_column_name}' already exists, it will be overwritten")
+        logger.warning(
+            f"Column '{metadata_column_name}' already exists, it will be overwritten"
+        )
         ds = ds.remove_columns([metadata_column_name])
     ds = ds.add_column(metadata_column_name, all_metadata)
 
     # Add inference information
-    inference_info = json.dumps({
-        "model": model,
-        "script": "olmocr2-vllm.py",
-        "version": "1.0.0",
-        "timestamp": datetime.now().isoformat(),
-        "batch_size": batch_size,
-        "max_tokens": max_tokens,
-        "temperature": temperature,
-    })
+    inference_info = json.dumps(
+        {
+            "model": model,
+            "script": "olmocr2-vllm.py",
+            "version": "1.0.0",
+            "timestamp": datetime.now().isoformat(),
+            "batch_size": batch_size,
+            "max_tokens": max_tokens,
+            "temperature": temperature,
+        }
+    )
 
     # Handle existing inference_info column
     if inference_info_column in ds.column_names: