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()