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import os | |
from huggingface_hub import HfApi | |
# Info to change for your repository | |
# ---------------------------------- | |
TOKEN = os.environ.get("HF_TOKEN") # A read/write token for your org | |
OWNER = "hebrew-llm-leaderboard" # Change to your org - don't forget to create a results and request file | |
# For harness evaluations | |
DEVICE = "cpu" # "cuda:0" if you add compute, for harness evaluations | |
LIMIT = None # !!!! Should be None for actual evaluations!!! | |
# For lighteval evaluations | |
ACCELERATOR = "gpu" | |
REGION = "us-east-1" | |
VENDOR = "aws" | |
# ---------------------------------- | |
# REPO_ID = f"{OWNER}/leaderboard-backend" | |
QUEUE_REPO = f"{OWNER}/requests" | |
RESULTS_REPO = f"{OWNER}/private-results" | |
# If you setup a cache later, just change HF_HOME | |
CACHE_PATH=os.getenv("HF_HOME", ".") | |
# Local caches | |
EVAL_REQUESTS_PATH = os.path.join(CACHE_PATH, "eval-queue") | |
EVAL_RESULTS_PATH = os.path.join(CACHE_PATH, "eval-results") | |
EVAL_REQUESTS_PATH_BACKEND = os.path.join(CACHE_PATH, "eval-queue-bk") | |
EVAL_RESULTS_PATH_BACKEND = os.path.join(CACHE_PATH, "eval-results-bk") | |
API = HfApi(token=TOKEN) | |