| import os | |
| from huggingface_hub import HfApi | |
| # ---------------------------------- | |
| TOKEN = os.environ.get("HF_TOKEN") # A read/write token for your org | |
| PERSPECTIVE_API_KEY = os.environ.get("PERSPECTIVE_API_KEY") | |
| OWNER = "meg" | |
| DEVICE = "cuda:0" #if you add compute, for harness evaluations | |
| EVAL_CUTOFF = 10 # !!!! For testing, should be None for actual evaluations!!! | |
| NUM_FEWSHOT = 0 # Change with your few shot for the Harness evaluations | |
| TASKS_HARNESS = ["realtoxicityprompts"]#, "toxigen", "logiqa"] | |
| # For lighteval evaluations | |
| ACCELERATOR = "cpu" | |
| REGION = "us-east-1" | |
| VENDOR = "aws" | |
| TASKS_LIGHTEVAL = "lighteval|anli:r1|0|0,lighteval|logiqa|0|0" | |
| # To add your own tasks, edit the custom file and launch it with `custom|myothertask|0|0`` | |
| # --------------------------------------------------- | |
| REPO_ID = f"{OWNER}/leaderboard" | |
| QUEUE_REPO = f"{OWNER}/requests" | |
| RESULTS_REPO = f"{OWNER}/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") | |
| REFRESH_RATE = 10 * 60 # 10 min | |
| NUM_LINES_VISUALIZE = 300 | |
| API = HfApi(token=TOKEN) | |