tokens

app.py

@@ -36,14 +36,14 @@ def restart_space():
 try:
     print(EVAL_REQUESTS_PATH)
     snapshot_download(
-        repo_id=QUEUE_REPO, local_dir=EVAL_REQUESTS_PATH, repo_type="dataset", tqdm_class=None, etag_timeout=30
+        repo_id=QUEUE_REPO, local_dir=EVAL_REQUESTS_PATH, repo_type="dataset", tqdm_class=None, token=TOKEN, etag_timeout=30
     )
 except Exception:
     restart_space()
 try:
     print(EVAL_RESULTS_PATH)
     snapshot_download(
-        repo_id=RESULTS_REPO, local_dir=EVAL_RESULTS_PATH, repo_type="dataset", tqdm_class=None, etag_timeout=30
+        repo_id=RESULTS_REPO, local_dir=EVAL_RESULTS_PATH, repo_type="dataset", tqdm_class=None, token=TOKEN, etag_timeout=30
     )
 except Exception:
     restart_space()

scripts/create_request_file.py

@@ -9,7 +9,7 @@ from colorama import Fore
 from huggingface_hub import HfApi, snapshot_download
 
 EVAL_REQUESTS_PATH = "eval-queue"
-QUEUE_REPO = "open-llm-leaderboard/requests"
+QUEUE_REPO = "logikon/cot-leaderboard-requests"
 
 precisions = ("float16", "bfloat16", "8bit (LLM.int8)", "4bit (QLoRA / FP4)", "GPTQ")
 model_types = ("pretrained", "fine-tuned", "RL-tuned", "instruction-tuned")

src/display/about.py

@@ -35,17 +35,21 @@ To reproduce our results, here is the commands you can run:
 EVALUATION_QUEUE_TEXT = """
 ## Some good practices before submitting a model
 
-### 1) Make sure you can load your model and tokenizer using AutoClasses:
+### 1) Make sure you can load your model and tokenizer with `vLLM`:
 ```python
-from transformers import AutoConfig, AutoModel, AutoTokenizer
-config = AutoConfig.from_pretrained("your model name", revision=revision)
-model = AutoModel.from_pretrained("your model name", revision=revision)
-tokenizer = AutoTokenizer.from_pretrained("your model name", revision=revision)
+from vllm import LLM, SamplingParams
+prompts = [
+    "Hello, my name is",
+    "The president of the United States is",
+    "The capital of France is",
+    "The future of AI is",
+]
+sampling_params = SamplingParams(temperature=0.8, top_p=0.95)
+llm = LLM(model="<USER>/<MODEL>")
 ```
 If this step fails, follow the error messages to debug your model before submitting it. It's likely your model has been improperly uploaded.
 
 Note: make sure your model is public!
-Note: if your model needs `use_remote_code=True`, we do not support this option yet but we are working on adding it, stay posted!
 
 ### 2) Convert your model weights to [safetensors](https://huggingface.co/docs/safetensors/index)
 It's a new format for storing weights which is safer and faster to load and use. It will also allow us to add the number of parameters of your model to the `Extended Viewer`!