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from src.display.formatting import model_hyperlink
from src.display.utils import AutoEvalColumn
# Models which have been flagged by users as being problematic for a reason or another
# (Model name to forum discussion link)
FLAGGED_MODELS = {
"Voicelab/trurl-2-13b": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/202",
"deepnight-research/llama-2-70B-inst": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/207",
"Aspik101/trurl-2-13b-pl-instruct_unload": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/213",
"Fredithefish/ReasonixPajama-3B-HF": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/236",
"TigerResearch/tigerbot-7b-sft-v1": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/237",
"gaodrew/gaodrew-gorgonzola-13b": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/215",
"AIDC-ai-business/Marcoroni-70B": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/287",
"AIDC-ai-business/Marcoroni-13B": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/287",
"AIDC-ai-business/Marcoroni-7B": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/287",
"TigerResearch/tigerbot-70b-chat-v4-4k": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/438",
"TigerResearch/tigerbot-70b-chat-v2": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/438",
}
# Models which have been requested by orgs to not be submitted on the leaderboard
DO_NOT_SUBMIT_MODELS = [
"Voicelab/trurl-2-13b", # trained on MMLU
"TigerResearch/tigerbot-70b-chat", # per authors request
"TigerResearch/tigerbot-70b-chat-v2", # per authors request
"TigerResearch/tigerbot-70b-chat-v4-4k", # per authors request
]
def flag_models(leaderboard_data: list[dict]):
for model_data in leaderboard_data:
if model_data["model_name_for_query"] in FLAGGED_MODELS:
issue_num = FLAGGED_MODELS[model_data["model_name_for_query"]].split("/")[-1]
issue_link = model_hyperlink(
FLAGGED_MODELS[model_data["model_name_for_query"]],
f"See discussion #{issue_num}",
)
model_data[
AutoEvalColumn.model.name
] = f"{model_data[AutoEvalColumn.model.name]} has been flagged! {issue_link}"
def remove_forbidden_models(leaderboard_data: list[dict]):
indices_to_remove = []
for ix, model in enumerate(leaderboard_data):
if model["model_name_for_query"] in DO_NOT_SUBMIT_MODELS:
indices_to_remove.append(ix)
for ix in reversed(indices_to_remove):
leaderboard_data.pop(ix)
return leaderboard_data
def filter_models(leaderboard_data: list[dict]):
leaderboard_data = remove_forbidden_models(leaderboard_data)
flag_models(leaderboard_data)
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