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[
{ "name":"SGPT-125M-Search",
"model":"Muennighoff/SGPT-125M-weightedmean-msmarco-specb-bitfit",
"fork_url":"https://github.com/taskswithcode/sgpt",
"orig_author_url":"https://github.com/Muennighoff",
"orig_author":"Niklas Muennighoff",
"sota_info": {
"task":"#1 in multiple information retrieval & search tasks(smaller variant)",
"sota_link":"https://paperswithcode.com/paper/sgpt-gpt-sentence-embeddings-for-semantic"
},
"paper_url":"https://arxiv.org/abs/2202.08904v5",
"mark":"True",
"class":"SGPTQnAModel"},
{ "name":"GPT-Neo-125M",
"model":"EleutherAI/gpt-neo-125M",
"fork_url":"https://github.com/taskswithcode/sgpt",
"orig_author_url":"https://www.eleuther.ai/",
"orig_author":"EleuthorAI",
"sota_info": {
"task":"Top 20 in multiple NLP tasks (smaller variant)",
"sota_link":"https://paperswithcode.com/paper/gpt-neox-20b-an-open-source-autoregressive-1"
},
"paper_url":"https://zenodo.org/record/5551208#.YyV0k-zMLX0",
"mark":"True",
"class":"CausalLMModel"},
{ "name":"sentence-transformers/all-MiniLM-L6-v2",
"model":"sentence-transformers/all-MiniLM-L6-v2",
"fork_url":"https://github.com/taskswithcode/sentence_similarity_hf_model",
"orig_author_url":"https://github.com/UKPLab",
"orig_author":"Ubiquitous Knowledge Processing Lab",
"sota_info": {
"task":"Over 3.8 million downloads from huggingface",
"sota_link":"https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2"
},
"paper_url":"https://arxiv.org/abs/1908.10084",
"mark":"True",
"class":"HFModel"},
{ "name":"sentence-transformers/paraphrase-MiniLM-L6-v2",
"model":"sentence-transformers/paraphrase-MiniLM-L6-v2",
"fork_url":"https://github.com/taskswithcode/sentence_similarity_hf_model",
"orig_author_url":"https://github.com/UKPLab",
"orig_author":"Ubiquitous Knowledge Processing Lab",
"sota_info": {
"task":"Over 2 million downloads from huggingface",
"sota_link":"https://huggingface.co/sentence-transformers/paraphrase-MiniLM-L6-v2"
},
"paper_url":"https://arxiv.org/abs/1908.10084",
"mark":"True",
"class":"HFModel"},
{ "name":"sentence-transformers/bert-base-nli-mean-tokens",
"model":"sentence-transformers/bert-base-nli-mean-tokens",
"fork_url":"https://github.com/taskswithcode/sentence_similarity_hf_model",
"orig_author_url":"https://github.com/UKPLab",
"orig_author":"Ubiquitous Knowledge Processing Lab",
"sota_info": {
"task":"Over 700,000 downloads from huggingface",
"sota_link":"https://huggingface.co/sentence-transformers/bert-base-nli-mean-tokens"
},
"paper_url":"https://arxiv.org/abs/1908.10084",
"mark":"True",
"class":"HFModel"},
{ "name":"sentence-transformers/all-mpnet-base-v2",
"model":"sentence-transformers/all-mpnet-base-v2",
"fork_url":"https://github.com/taskswithcode/sentence_similarity_hf_model",
"orig_author_url":"https://github.com/UKPLab",
"orig_author":"Ubiquitous Knowledge Processing Lab",
"sota_info": {
"task":"Over 500,000 downloads from huggingface",
"sota_link":"https://huggingface.co/sentence-transformers/all-mpnet-base-v2"
},
"paper_url":"https://arxiv.org/abs/1908.10084",
"mark":"True",
"class":"HFModel"},
{ "name":"sentence-transformers/all-MiniLM-L12-v2",
"model":"sentence-transformers/all-MiniLM-L12-v2",
"fork_url":"https://github.com/taskswithcode/sentence_similarity_hf_model",
"orig_author_url":"https://github.com/UKPLab",
"orig_author":"Ubiquitous Knowledge Processing Lab",
"sota_info": {
"task":"Over 500,000 downloads from huggingface",
"sota_link":"https://huggingface.co/sentence-transformers/all-MiniLM-L12-v2"
},
"paper_url":"https://arxiv.org/abs/1908.10084",
"mark":"True",
"class":"HFModel"},
{ "name":"SGPT-125M",
"model":"Muennighoff/SGPT-125M-weightedmean-nli-bitfit",
"fork_url":"https://github.com/taskswithcode/sgpt",
"orig_author_url":"https://github.com/Muennighoff",
"orig_author":"Niklas Muennighoff",
"sota_info": {
"task":"#1 in multiple information retrieval & search tasks(smaller variant)",
"sota_link":"https://paperswithcode.com/paper/sgpt-gpt-sentence-embeddings-for-semantic"
},
"paper_url":"https://arxiv.org/abs/2202.08904v5",
"mark":"True",
"class":"SGPTModel"},
{ "name":"SIMCSE-base" ,
"model":"princeton-nlp/sup-simcse-roberta-base",
"fork_url":"https://github.com/taskswithcode/SimCSE",
"orig_author_url":"https://github.com/princeton-nlp",
"orig_author":"Princeton Natural Language Processing",
"sota_info": {
"task":"Within top 10 in multiple semantic textual similarity tasks(smaller variant)",
"sota_link":"https://paperswithcode.com/paper/simcse-simple-contrastive-learning-of"
},
"paper_url":"https://arxiv.org/abs/2104.08821v4",
"mark":"True",
"class":"SimCSEModel","sota_link":"https://paperswithcode.com/sota/semantic-textual-similarity-on-sick"}
]
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