change repo

src/envs.py

@@ -5,13 +5,13 @@ from huggingface_hub import HfApi
 # clone / pull the lmeh eval data
 H4_TOKEN = os.environ.get("H4_TOKEN", None)
 
-REPO_ID = "HuggingFaceH4/open_llm_leaderboard"
-QUEUE_REPO = "open-llm-leaderboard/requests"
-DYNAMIC_INFO_REPO = "open-llm-leaderboard/dynamic_model_information"
-RESULTS_REPO = "open-llm-leaderboard/results"
+REPO_ID = "BAAI/open_cn_llm_leaderboard"
+QUEUE_REPO = "open_cn_llm_leaderboard/requests"
+DYNAMIC_INFO_REPO = "open_cn_llm_leaderboard/dynamic_model_information"
+RESULTS_REPO = "open_cn_llm_leaderboard/results"
 
-PRIVATE_QUEUE_REPO = "open-llm-leaderboard/private-requests"
-PRIVATE_RESULTS_REPO = "open-llm-leaderboard/private-results"
+PRIVATE_QUEUE_REPO = "open_cn_llm_leaderboard/private-requests"
+PRIVATE_RESULTS_REPO = "open_cn_llm_leaderboard/private-results"
 
 IS_PUBLIC = bool(os.environ.get("IS_PUBLIC", True))
 
@@ -25,7 +25,7 @@ DYNAMIC_INFO_FILE_PATH = os.path.join(DYNAMIC_INFO_PATH, "model_infos.json")
 EVAL_REQUESTS_PATH_PRIVATE = "eval-queue-private"
 EVAL_RESULTS_PATH_PRIVATE = "eval-results-private"
 
-PATH_TO_COLLECTION = "open-llm-leaderboard/llm-leaderboard-best-models-652d6c7965a4619fb5c27a03"
+PATH_TO_COLLECTION = "open_cn_llm_leaderboard/llm-leaderboard-best-models-652d6c7965a4619fb5c27a03"
 
 # Rate limit variables
 RATE_LIMIT_PERIOD = 7

src/scripts/create_request_file.py

@@ -11,7 +11,7 @@ from src.submission.check_validity import get_model_size
 from src.display.utils import ModelType, WeightType
 
 EVAL_REQUESTS_PATH = "eval-queue"
-QUEUE_REPO = "open-llm-leaderboard/requests"
+QUEUE_REPO = "open_cn_llm_leaderboard/requests"
 
 precisions = ("float16", "bfloat16", "8bit (LLM.int8)", "4bit (QLoRA / FP4)", "GPTQ")
 model_types = [e.name for e in ModelType]