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Download src/envs.py from EmbodiedAgentInterface/backend: direct link, hf CLI and curl.
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- Download file 1.06 kB
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https://huggingface.co/spaces/EmbodiedAgentInterface/backend/resolve/da4c3ac86bdec340ea7cd73de405becf8e9e59a2/src/envs.py
- Command line
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hf download hf://spaces/EmbodiedAgentInterface/backend@da4c3ac86bdec340ea7cd73de405becf8e9e59a2/src/envs.py
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curl -L -o envs.py https://huggingface.co/spaces/EmbodiedAgentInterface/backend/resolve/da4c3ac86bdec340ea7cd73de405becf8e9e59a2/src/envs.py
1.06 kB
| import os | |
| from huggingface_hub import HfApi | |
| # Info to change for your repository | |
| # ---------------------------------- | |
| TOKEN = os.environ.get("TOKEN") # A read/write token for your org | |
| OWNER = "demo-leaderboard-backend" # 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 = 20 # !!!! Should be None for actual evaluations!!! | |
| # For lighteval evaluations | |
| ACCELERATOR = "" | |
| REGION = "" | |
| VENDOR = "" | |
| # ---------------------------------- | |
| REPO_ID = f"{OWNER}/leaderboard-backend" | |
| 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") | |
| API = HfApi(token=TOKEN) | |