Rename

src/envs.py

@@ -5,7 +5,7 @@ from huggingface_hub import HfApi
 
 # Info to change for your repository
 # ----------------------------------
-TOKEN = os.environ.get("HF_TOKEN")  # A read/write token for your org
+HF_TOKEN = os.environ.get("HF_TOKEN")  # A read/write token for your org
 
 OWNER = "llm-jp"  # Change to your org - don't forget to create a results and request dataset, with the correct format!
 # ----------------------------------
@@ -20,4 +20,4 @@ CACHE_PATH = pathlib.Path(os.getenv("HF_HOME", "."))
 # Local caches
 EVAL_REQUESTS_PATH = CACHE_PATH / "eval-queue"
 
-API = HfApi(token=TOKEN)
+API = HfApi(token=HF_TOKEN)

src/submission/submit.py

@@ -3,7 +3,7 @@ from datetime import datetime, timezone
 
 from src.display.formatting import styled_error, styled_message, styled_warning
 from src.display.utils import EvalQueuedModel, LLMJpEvalVersion, VllmVersion
-from src.envs import API, EVAL_REQUESTS_PATH, QUEUE_REPO, TOKEN
+from src.envs import API, EVAL_REQUESTS_PATH, HF_TOKEN, QUEUE_REPO
 from src.submission.check_validity import already_submitted_models, check_model_card, is_model_on_hub
 
 REQUESTED_MODELS: set[EvalQueuedModel] = set()
@@ -48,7 +48,9 @@ def add_new_eval(
         return styled_error("Please select a model type.")
 
     # Is the model on the hub?
-    model_on_hub, error, _ = is_model_on_hub(model_name=model_id, revision=revision, token=TOKEN, test_tokenizer=True)
+    model_on_hub, error, _ = is_model_on_hub(
+        model_name=model_id, revision=revision, token=HF_TOKEN, test_tokenizer=True
+    )
     if not model_on_hub:
         return styled_error(f'Model "{model_id}" {error}')