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Download src/envs.py from TemryL/LLM-Disease-Risk-Leaderboard: direct link, hf CLI and curl.
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- Download file 897 Bytes
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https://huggingface.co/spaces/TemryL/LLM-Disease-Risk-Leaderboard/resolve/main/src/envs.py
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hf download hf://spaces/TemryL/LLM-Disease-Risk-Leaderboard/src/envs.py
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curl -L -o envs.py https://huggingface.co/spaces/TemryL/LLM-Disease-Risk-Leaderboard/resolve/main/src/envs.py
897 Bytes
| import os | |
| from huggingface_hub import HfApi | |
| # Info to change for your repository | |
| # ---------------------------------- | |
| HF_TOKEN = os.environ.get("HF_TOKEN") # A read/write token for your org | |
| OWNER = "TemryL" # Change to your org - don't forget to create a results and request dataset, with the correct format! | |
| # ---------------------------------- | |
| REPO_ID = f"{OWNER}/LLM-Disease-Risk-Leaderboard" | |
| QUEUE_REPO = f"{OWNER}/LLM-Disease-Risk-Requests" | |
| RESULTS_REPO = f"{OWNER}/LLM-Disease-Risk-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=HF_TOKEN) | |