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File size: 1,410 Bytes
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import os
from yaml import safe_load
from huggingface_hub import HfApi
LEADERBOARD_CONFIG_PATH = "config.yaml"
with open(LEADERBOARD_CONFIG_PATH, 'r', encoding='utf-8') as f:
LEADERBOARD_CONFIG = safe_load(f)
MODEL_META_PATH = "model_meta.yaml"
with open(MODEL_META_PATH, 'r', encoding='utf-8') as f:
MODEL_META = safe_load(f)
# Try first to get the config from the environment variables, then from the config.yaml file
def get_config(name, default):
res = None
if name in os.environ:
res = os.environ[name]
elif 'config' in LEADERBOARD_CONFIG:
res = LEADERBOARD_CONFIG['config'].get(name, None)
if res is None:
return default
return res
def str2bool(v):
return str(v).lower() in ("yes", "true", "t", "1")
# clone / pull the lmeh eval data
HF_TOKEN = get_config("HF_TOKEN", None)
LEADERBOARD_NAME = get_config("LEADERBOARD_NAME", "MTEB Leaderboard")
REPO_ID = get_config("REPO_ID", "mteb/leaderboard")
RESULTS_REPO = get_config("RESULTS_REPO", "mteb/results")
CACHE_PATH=get_config("HF_HOME", ".")
os.environ["HF_HOME"] = CACHE_PATH
# Check if it is using persistent storage
if not os.access(CACHE_PATH, os.W_OK):
print(f"No write access to HF_HOME: {CACHE_PATH}. Resetting to current directory.")
CACHE_PATH = "."
os.environ["HF_HOME"] = CACHE_PATH
else:
print(f"Write access confirmed for HF_HOME")
API = HfApi(token=HF_TOKEN) |