taskswithcode/semantic_search
2
1[2 3 { "name":"sentence-transformers/all-MiniLM-L6-v2", 4 "model":"sentence-transformers/all-MiniLM-L6-v2",5 "fork_url":"https://github.com/taskswithcode/sentence_similarity_hf_model",6 "orig_author_url":"https://github.com/UKPLab",7 "orig_author":"Ubiquitous Knowledge Processing Lab",8 "sota_info": { 9 "task":"Over 3.8 million downloads from huggingface",10 "sota_link":"https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2"11 },12 "paper_url":"https://arxiv.org/abs/1908.10084",13 "mark":"True",14 "class":"HFModel"},15 { "name":"sentence-transformers/paraphrase-MiniLM-L6-v2", 16 "model":"sentence-transformers/paraphrase-MiniLM-L6-v2",17 "fork_url":"https://github.com/taskswithcode/sentence_similarity_hf_model",18 "orig_author_url":"https://github.com/UKPLab",19 "orig_author":"Ubiquitous Knowledge Processing Lab",20 "sota_info": { 21 "task":"Over 2 million downloads from huggingface",22 "sota_link":"https://huggingface.co/sentence-transformers/paraphrase-MiniLM-L6-v2"23 },24 "paper_url":"https://arxiv.org/abs/1908.10084",25 "mark":"True",26 "class":"HFModel"},27 { "name":"sentence-transformers/bert-base-nli-mean-tokens", 28 "model":"sentence-transformers/bert-base-nli-mean-tokens",29 "fork_url":"https://github.com/taskswithcode/sentence_similarity_hf_model",30 "orig_author_url":"https://github.com/UKPLab",31 "orig_author":"Ubiquitous Knowledge Processing Lab",32 "sota_info": { 33 "task":"Over 700,000 downloads from huggingface",34 "sota_link":"https://huggingface.co/sentence-transformers/bert-base-nli-mean-tokens"35 },36 "paper_url":"https://arxiv.org/abs/1908.10084",37 "mark":"True",38 "class":"HFModel"},39 { "name":"sentence-transformers/all-mpnet-base-v2", 40 "model":"sentence-transformers/all-mpnet-base-v2",41 "fork_url":"https://github.com/taskswithcode/sentence_similarity_hf_model",42 "orig_author_url":"https://github.com/UKPLab",43 "orig_author":"Ubiquitous Knowledge Processing Lab",44 "sota_info": { 45 "task":"Over 500,000 downloads from huggingface",46 "sota_link":"https://huggingface.co/sentence-transformers/all-mpnet-base-v2"47 },48 "paper_url":"https://arxiv.org/abs/1908.10084",49 "mark":"True",50 "class":"HFModel"},51 { "name":"sentence-transformers/all-MiniLM-L12-v2",52 "model":"sentence-transformers/all-MiniLM-L12-v2",53 "fork_url":"https://github.com/taskswithcode/sentence_similarity_hf_model",54 "orig_author_url":"https://github.com/UKPLab",55 "orig_author":"Ubiquitous Knowledge Processing Lab",56 "sota_info": { 57 "task":"Over 500,000 downloads from huggingface",58 "sota_link":"https://huggingface.co/sentence-transformers/all-MiniLM-L12-v2"59 },60 "paper_url":"https://arxiv.org/abs/1908.10084",61 "mark":"True",62 "class":"HFModel"},63 64 { "name":"SGPT-125M", 65 "model":"Muennighoff/SGPT-125M-weightedmean-nli-bitfit",66 "fork_url":"https://github.com/taskswithcode/sgpt",67 "orig_author_url":"https://github.com/Muennighoff",68 "orig_author":"Niklas Muennighoff",69 "sota_info": { 70 "task":"#1 in multiple information retrieval & search tasks(smaller variant)",71 "sota_link":"https://paperswithcode.com/paper/sgpt-gpt-sentence-embeddings-for-semantic"72 },73 "paper_url":"https://arxiv.org/abs/2202.08904v5",74 "mark":"True",75 "class":"SGPTModel"},76 { "name":"SGPT-1.3B",77 "model": "Muennighoff/SGPT-1.3B-weightedmean-msmarco-specb-bitfit",78 "fork_url":"https://github.com/taskswithcode/sgpt",79 "orig_author_url":"https://github.com/Muennighoff",80 "orig_author":"Niklas Muennighoff",81 "sota_info": { 82 "task":"#1 in multiple information retrieval & search tasks(smaller variant)",83 "sota_link":"https://paperswithcode.com/paper/sgpt-gpt-sentence-embeddings-for-semantic"84 },85 "paper_url":"https://arxiv.org/abs/2202.08904v5",86 "Note":"If this large model takes too long or fails to load , try this ",87 "alt_url":"http://www.taskswithcode.com/sentence_similarity/",88 "mark":"True",89 "class":"SGPTModel"},90 { "name":"SGPT-5.8B",91 "model": "Muennighoff/SGPT-5.8B-weightedmean-msmarco-specb-bitfit" ,92 "fork_url":"https://github.com/taskswithcode/sgpt",93 "orig_author_url":"https://github.com/Muennighoff",94 "orig_author":"Niklas Muennighoff",95 "Note":"If this large model takes too long or fails to load , try this ",96 "alt_url":"http://www.taskswithcode.com/sentence_similarity/",97 "sota_info": { 98 "task":"#1 in multiple information retrieval & search tasks",99 "sota_link":"https://paperswithcode.com/paper/sgpt-gpt-sentence-embeddings-for-semantic"100 },101 "paper_url":"https://arxiv.org/abs/2202.08904v5",102 "mark":"True",103 "class":"SGPTModel"},104 105 { "name":"SIMCSE-large" ,106 "model":"princeton-nlp/sup-simcse-roberta-large",107 "fork_url":"https://github.com/taskswithcode/SimCSE",108 "orig_author_url":"https://github.com/princeton-nlp",109 "orig_author":"Princeton Natural Language Processing",110 "Note":"If this large model takes too long or fails to load , try this ",111 "alt_url":"http://www.taskswithcode.com/sentence_similarity/",112 "sota_info": { 113 "task":"Within top 10 in multiple semantic textual similarity tasks",114 "sota_link":"https://paperswithcode.com/paper/simcse-simple-contrastive-learning-of"115 },116 "paper_url":"https://arxiv.org/abs/2104.08821v4",117 "mark":"True",118 "class":"SimCSEModel","sota_link":"https://paperswithcode.com/sota/semantic-textual-similarity-on-sick"},119 120 { "name":"SIMCSE-base" ,121 "model":"princeton-nlp/sup-simcse-roberta-base",122 "fork_url":"https://github.com/taskswithcode/SimCSE",123 "orig_author_url":"https://github.com/princeton-nlp",124 "orig_author":"Princeton Natural Language Processing",125 "sota_info": { 126 "task":"Within top 10 in multiple semantic textual similarity tasks(smaller variant)",127 "sota_link":"https://paperswithcode.com/paper/simcse-simple-contrastive-learning-of"128 },129 "paper_url":"https://arxiv.org/abs/2104.08821v4",130 "mark":"True",131 "class":"SimCSEModel","sota_link":"https://paperswithcode.com/sota/semantic-textual-similarity-on-sick"}132 133 134 ]135