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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 = [
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/intfloat/multilingual-e5-large-instruct">multilingual-e5-large-instruct</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/facebook/SONAR">SONAR</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/sentence-transformers/LaBSE">LaBSE</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/intfloat/multilingual-e5-large">multilingual-e5-large</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/intfloat/e5-mistral-7b-instruct">e5-mistral-7b-instruct</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/intfloat/multilingual-e5-base">multilingual-e5-base</a>',
'<a target="_blank" style="text-decoration: underline" href="https://github.com/facebookresearch/LASER">LASER2</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/intfloat/multilingual-e5-small">multilingual-e5-small</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/sentence-transformers/paraphrase-multilingual-mpnet-base-v2">paraphrase-multilingual-mpnet-base-v2</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2">paraphrase-multilingual-MiniLM-L12-v2</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/izhx/udever-bloom-7b1">udever-bloom-7b1</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/izhx/udever-bloom-3b">udever-bloom-3b</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/bigscience/sgpt-bloom-7b1-msmarco">sgpt-bloom-7b1-msmarco</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/izhx/udever-bloom-1b1">udever-bloom-1b1</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/izhx/udever-bloom-560m">udever-bloom-560m</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/sentence-transformers/sentence-t5-xl">sentence-t5-xl</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/sentence-transformers/gtr-t5-xl">gtr-t5-xl</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/ClayAtlas/winberta-base">winberta-base</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/sentence-transformers/sentence-t5-large">sentence-t5-large</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/avsolatorio/GIST-Embedding-v0">GIST-Embedding-v0</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/sentence-transformers/average_word_embeddings_komninos">komninos</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/DMetaSoul/sbert-chinese-general-v1">sbert-chinese-general-v1</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/Muennighoff/SGPT-125M-weightedmean-nli-bitfit">SGPT-125M-weightedmean-nli-bitfit</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/Muennighoff/SGPT-5.8B-weightedmean-nli-bitfit">SGPT-5.8B-weightedmean-nli-bitfit</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/jinaai/jina-embeddings-v2-base-de">jina-embeddings-v2-base-de</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/sentence-transformers/average_word_embeddings_glove.6B.300d">glove.6B.300d</a>',
'<a target="_blank" style="text-decoration: underline" href="https://huggingface.co/zhou-xl/bi-cse">bi-cse</a>',
]
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,
column_widths=["2%", "33%"]
)
if __name__ == "__main__":
demo.launch()