fix typo

tasks/text.py

@@ -35,7 +35,7 @@ class TextClassifier:
     def __init__(self):
         self.device = "cuda" if torch.cuda.is_available() else "cpu"
         max_retries = 3
-        model_name = "Tonic/climate-guard-toxic-agent"
+        model_name = "answerdotai/ModernBERT-base"
         
         for attempt in range(max_retries):
             try:
@@ -111,6 +111,7 @@ class TextClassifier:
             del self.model
         if torch.cuda.is_available():
             torch.cuda.empty_cache()
+    
 
 @router.post(ROUTE, tags=["Text Task"], description=DESCRIPTION)
 async def evaluate_text(request: TextEvaluationRequest):
@@ -133,7 +134,7 @@ async def evaluate_text(request: TextEvaluationRequest):
 
     try:
         # Load and prepare the dataset
-        dataset = load_dataset(request.dataset_name)
+        dataset = load_dataset("QuotaClimat/frugalaichallenge-text-train", token=HF_TOKEN)
         
         # Convert string labels to integers
         dataset = dataset.map(lambda x: {"label": LABEL_MAPPING[x["label"]]})
@@ -151,7 +152,7 @@ async def evaluate_text(request: TextEvaluationRequest):
         classifier = TextClassifier()
 
         # Prepare batches
-        batch_size = 16  # Reduced batch size
+        batch_size = 24
         quotes = test_dataset["quote"]
         num_batches = len(quotes) // batch_size + (1 if len(quotes) % batch_size != 0 else 0)
         batches = [
@@ -163,7 +164,7 @@ async def evaluate_text(request: TextEvaluationRequest):
         batch_results = [[] for _ in range(num_batches)]
         
         # Process batches in parallel
-        max_workers = min(os.cpu_count(), 2)  # Reduced workers
+        max_workers = min(os.cpu_count(), 4)
         print(f"Processing with {max_workers} workers")
         
         with ThreadPoolExecutor(max_workers=max_workers) as executor:
@@ -219,4 +220,5 @@ async def evaluate_text(request: TextEvaluationRequest):
 
     except Exception as e:
         print(f"Error in evaluate_text: {str(e)}")
-        raise Exception(f"Failed to process request: {str(e)}")
+        raise Exception(f"Failed to process request: {str(e)}")
+