[
            {   "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"},
            {  "name":"GPT-3-175B (text-search-davinci-doc-001)" ,
                "model":"text-search-davinci-doc-001",
                "fork_url":"https://openai.com/api/",
                "orig_author_url":"https://openai.com/api/",
                "orig_author":"OpenAI",
                "sota_info": {   
                                 "task":"GPT-3 achieves strong zero-shot and few-shot performance on many NLP datasets etc.",
                                 "sota_link":"https://paperswithcode.com/method/gpt-3"
                            },
                "paper_url":"https://arxiv.org/abs/2005.14165v4",
                "mark":"True",
                "custom_load":"False",
                "Note":"Custom file upload requires OpenAI API access to create embeddings. For API access, use this link ",
                "alt_url":"https://openai.com/api/",
                "class":"OpenAIQnAModel","sota_link":"https://arxiv.org/abs/2005.14165v4"},
            {  "name":"GPT-3-6.7B (text-search-curie-doc-001)" ,
                "model":"text-search-curie-doc-001",
                "fork_url":"https://openai.com/api/",
                "orig_author_url":"https://openai.com/api/",
                "orig_author":"OpenAI",
                "sota_info": {   
                                 "task":"GPT-3 achieves strong zero-shot and few-shot performance on many NLP datasets etc.",
                                 "sota_link":"https://paperswithcode.com/method/gpt-3"
                            },
                "paper_url":"https://arxiv.org/abs/2005.14165v4",
                "mark":"True",
                "custom_load":"False",
                "Note":"Custom file upload requires OpenAI API access to create embeddings. For API access, use this link ",
                "alt_url":"https://openai.com/api/",
                "class":"OpenAIQnAModel","sota_link":"https://arxiv.org/abs/2005.14165v4"},
            {  "name":"GPT-3-1.3B (text-search-babbage-doc-001)" ,
                "model":"text-search-babbage-doc-001",
                "fork_url":"https://openai.com/api/",
                "orig_author_url":"https://openai.com/api/",
                "orig_author":"OpenAI",
                "sota_info": {   
                                 "task":"GPT-3 achieves strong zero-shot and few-shot performance on many NLP datasets etc.",
                                 "sota_link":"https://paperswithcode.com/method/gpt-3"
                            },
                "paper_url":"https://arxiv.org/abs/2005.14165v4",
                "mark":"True",
                "custom_load":"False",
                "Note":"Custom file upload requires OpenAI API access to create embeddings. For API access, use this link ",
                "alt_url":"https://openai.com/api/",
                "class":"OpenAIQnAModel","sota_link":"https://arxiv.org/abs/2005.14165v4"},
            {  "name":"GPT-3-350M (text-search-ada-doc-001)" ,
                "model":"text-search-ada-doc-001",
                "fork_url":"https://openai.com/api/",
                "orig_author_url":"https://openai.com/api/",
                "orig_author":"OpenAI",
                "sota_info": {   
                                 "task":"GPT-3 achieves strong zero-shot and few-shot performance on many NLP datasets etc.",
                                 "sota_link":"https://paperswithcode.com/method/gpt-3"
                            },
                "paper_url":"https://arxiv.org/abs/2005.14165v4",
                "mark":"True",
                "custom_load":"False",
                "Note":"Custom file upload requires OpenAI API access to create embeddings. For API access, use this link ",
                "alt_url":"https://openai.com/api/",
                "class":"OpenAIQnAModel","sota_link":"https://arxiv.org/abs/2005.14165v4"}


            ]