Update scripts/create_request_file.py

scripts/create_request_file.py

@@ -9,7 +9,7 @@ from colorama import Fore
 from huggingface_hub import HfApi, snapshot_download
 
 EVAL_REQUESTS_PATH = "eval-queue"
-QUEUE_REPO = "open-llm-leaderboard/requests"
+QUEUE_REPO = "le-leadboard/requests"
 
 precisions = ("float16", "bfloat16", "8bit (LLM.int8)", "4bit (QLoRA / FP4)", "GPTQ")
 model_types = ("pretrained", "fine-tuned", "RL-tuned", "instruction-tuned")
@@ -38,13 +38,14 @@ def main():
     current_time = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")
     snapshot_download(repo_id=QUEUE_REPO, revision="main", local_dir=EVAL_REQUESTS_PATH, repo_type="dataset")
 
-    model_name = click.prompt("Enter model name")
-    revision = click.prompt("Enter revision", default="main")
-    precision = click.prompt("Enter precision", default="float16", type=click.Choice(precisions))
-    model_type = click.prompt("Enter model type", type=click.Choice(model_types))
-    weight_type = click.prompt("Enter weight type", default="Original", type=click.Choice(weight_types))
-    base_model = click.prompt("Enter base model", default="")
-    status = click.prompt("Enter status", default="FINISHED")
+    model_name = click.prompt("Entrez le nom du modèle")
+    revision = click.prompt("Entrez la révision", default="main")
+    precision = click.prompt("Entrez la précision", default="float16", type=click.Choice(precisions))
+    model_type = click.prompt("Entrez le type de modèle", type=click.Choice(model_types))
+    weight_type = click.prompt("Entrez le type de poids", default="Original", type=click.Choice(weight_types))
+    base_model = click.prompt("Entrez le modèle de base", default="")
+    status = click.prompt("Entrez le statut", default="FINISHED")
+
 
     try:
         model_info = api.model_info(repo_id=model_name, revision=revision)