import gradio as gr
headers = [
"Rank",
"Model",
"Average",
"STS12",
"STS13",
"STS14",
"STS15",
"STS16",
"SICK-E",
"SICK-F",
"STS-B",
"STS12",
"STS13",
"STS14",
"STS15",
"STS16",
"SICK-R",
"STS-B",
"STS12",
]
list = [
'multilingual-e5-large-instruct',
'SONAR',
'LaBSE',
'multilingual-e5-large',
'e5-mistral-7b-instruct',
'multilingual-e5-base',
'LASER2',
'multilingual-e5-small',
'paraphrase-multilingual-mpnet-base-v2',
'paraphrase-multilingual-MiniLM-L12-v2',
'udever-bloom-7b1',
'udever-bloom-3b',
'sgpt-bloom-7b1-msmarco',
'udever-bloom-1b1',
'udever-bloom-560m',
'sentence-t5-xl',
'gtr-t5-xl',
'winberta-base',
'sentence-t5-large',
'GIST-Embedding-v0',
'komninos',
'sbert-chinese-general-v1',
'SGPT-125M-weightedmean-nli-bitfit',
'SGPT-5.8B-weightedmean-nli-bitfit',
'jina-embeddings-v2-base-de',
'glove.6B.300d',
'bi-cse',
]
def make_long_table():
new_list = []
for i in enumerate(list):
new_list.append([i[0], i[1]] + [i[0]] * 16)
return {"headers": headers, "data": new_list}
with gr.Blocks() as demo:
gr.Dataframe(
value=make_long_table(),
datatype=["number", "html"] + ["number"] * 16,
)
if __name__ == "__main__":
demo.launch()