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| model_meta: | |
| sentence-transformers/all-MiniLM-L6-v2: | |
| link: https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2 | |
| revision: 8b3219a92973c328a8e22fadcfa821b5dc75636a | |
| desc: all-MiniLM-L6-v2 by Sentence Transformers | |
| seq_len: 512 | |
| size: 23 | |
| dim: 384 | |
| license: Apache 2.0 | |
| organization: Sentence Transformers | |
| mteb_overall: 56.26 | |
| mteb_retrieval: 41.95 | |
| mteb_sts: 78.90 | |
| mteb_clustering: 42.35 | |
| intfloat/multilingual-e5-small: | |
| link: https://huggingface.co/intfloat/multilingual-e5-small | |
| revision: e4ce9877abf3edfe10b0d82785e83bdcb973e22e | |
| desc: multilingual-e5-small by Microsoft | |
| seq_len: 512 | |
| size: 44 | |
| dim: 384 | |
| license: MIT License | |
| organization: Microsoft | |
| mteb_overall: 57.87 | |
| mteb_retrieval: 46.64 | |
| mteb_sts: 79.10 | |
| mteb_clustering: 37.08 | |
| intfloat/multilingual-e5-large-instruct: | |
| link: https://huggingface.co/intfloat/multilingual-e5-large-instruct | |
| revision: baa7be480a7de1539afce709c8f13f833a510e0a | |
| desc: multilingual-e5-large-instruct by Microsoft | |
| seq_len: 514 | |
| size: 560 | |
| dim: 1024 | |
| license: MIT License | |
| organization: Microsoft | |
| instruction_query_arxiv: Given a query, retrieve a relevant paper title and abstract from arXiv | |
| instruction_query_wikipedia: Given a query, retrieve a relevant title and passage from Wikipedia | |
| instruction_query_stackexchange: Given a query, retrieve a relevant question and answer from Stack Exchange | |
| instruction_sts: Retrieve semantically similar text | |
| instruction_clustering: Identify the topic/theme/category of the text | |
| mteb_overall: 64.41 | |
| mteb_retrieval: 52.47 | |
| mteb_sts: 84.78 | |
| mteb_clustering: 47.10 | |
| intfloat/e5-mistral-7b-instruct: | |
| link: https://huggingface.co/intfloat/e5-mistral-7b-instruct | |
| revision: 07163b72af1488142a360786df853f237b1a3ca1 | |
| desc: e5-mistral-7b-instruct by Microsoft | |
| seq_len: 32768 | |
| size: 7111 | |
| dim: 4096 | |
| license: MIT License | |
| organization: Microsoft | |
| instruction_query_arxiv: Given a query, retrieve a relevant paper title and abstract from arXiv | |
| instruction_query_wikipedia: Given a query, retrieve a relevant title and passage from Wikipedia | |
| instruction_query_stackexchange: Given a query, retrieve a relevant question and answer from Stack Exchange | |
| instruction_sts: Retrieve semantically similar text | |
| instruction_clustering: Identify the topic/theme/category of the text | |
| mteb_overall: 66.63 | |
| mteb_retrieval: 56.89 | |
| mteb_sts: 84.63 | |
| mteb_clustering: 50.26 | |
| GritLM/GritLM-7B: | |
| link: https://huggingface.co/GritLM/GritLM-7B | |
| revision: 13f00a0e36500c80ce12870ea513846a066004af | |
| desc: GritLM-7B by Contextual AI, HKU, Microsoft | |
| seq_len: 32768 | |
| size: 7240 | |
| dim: 4096 | |
| license: Apache 2.0 | |
| organization: Contextual AI, HKU, Microsoft | |
| instruction_query_arxiv: Given a query, retrieve a relevant paper title and abstract from arXiv | |
| instruction_query_wikipedia: Given a query, retrieve a relevant title and passage from Wikipedia | |
| instruction_query_stackexchange: Given a query, retrieve a relevant question and answer from Stack Exchange | |
| instruction_sts: Retrieve semantically similar text | |
| instruction_clustering: Identify the topic/theme/category of the text | |
| mteb_overall: 66.76 | |
| mteb_retrieval: 57.41 | |
| mteb_sts: 83.35 | |
| mteb_clustering: 50.61 | |
| BAAI/bge-large-en-v1.5: | |
| link: https://huggingface.co/BAAI/bge-large-en-v1.5 | |
| revision: d4aa6901d3a41ba39fb536a557fa166f842b0e09 | |
| desc: bge-large-en-v1.5 by BAAI | |
| seq_len: 512 | |
| size: 335 | |
| dim: 1024 | |
| license: MIT | |
| organization: BAAI | |
| mteb_overall: 64.23 | |
| mteb_retrieval: 54.29 | |
| mteb_sts: 83.11 | |
| mteb_clustering: 46.08 | |
| nvidia/NV-Embed-v1: | |
| link: https://huggingface.co/nvidia/NV-Embed-v1 | |
| revision: 77b11725df91ca45663471a0f2ec6c06e04cbadb | |
| desc: NV-Embed-v1 by Nvidia | |
| seq_len: 32768 | |
| size: 7851 | |
| dim: 4096 | |
| license: CC-BY-NC-4.0 | |
| organization: Nvidia | |
| mteb_overall: 69.32 | |
| mteb_retrieval: 59.36 | |
| mteb_sts: 82.84 | |
| mteb_clustering: 52.8 | |
| Alibaba-NLP/gte-Qwen2-7B-instruct: | |
| link: https://huggingface.co/Alibaba-NLP/gte-Qwen2-7B-instruct | |
| revision: e26182b2122f4435e8b3ebecbf363990f409b45b | |
| desc: gte-Qwen2-7B-instruct by Alibaba | |
| seq_len: 131072 | |
| size: 7613 | |
| dim: 3584 | |
| license: Apache 2.0 | |
| organization: Alibaba | |
| instruction_query_arxiv: Given a query, retrieve a relevant paper title and abstract from arXiv | |
| instruction_query_wikipedia: Given a query, retrieve a relevant title and passage from Wikipedia | |
| instruction_query_stackexchange: Given a query, retrieve a relevant question and answer from Stack Exchange | |
| instruction_clustering: Identify the topic/theme/category of the text | |
| instruction_sts: Retrieve semantically similar text | |
| mteb_overall: 70.24 | |
| mteb_retrieval: 60.25 | |
| mteb_sts: 83.04 | |
| mteb_clustering: 56.92 | |
| Salesforce/SFR-Embedding-2_R: | |
| link: https://huggingface.co/Salesforce/SFR-Embedding-2_R | |
| revision: 91762139d94ed4371a9fa31db5551272e0b83818 | |
| desc: SFR-Embedding-2_R by Salesforce | |
| seq_len: 32768 | |
| size: 7111 | |
| dim: 4096 | |
| license: CC-BY-NC-4.0 | |
| organization: Salesforce | |
| instruction_query_arxiv: Given a query, retrieve a relevant paper title and abstract from arXiv | |
| instruction_query_wikipedia: Given a query, retrieve a relevant title and passage from Wikipedia | |
| instruction_query_stackexchange: Given a query, retrieve a relevant question and answer from Stack Exchange | |
| instruction_clustering: Identify the topic/theme/category of the text | |
| instruction_sts: Retrieve semantically similar text | |
| mteb_overall: 70.31 | |
| mteb_retrieval: 60.18 | |
| mteb_sts: 81.26 | |
| mteb_clustering: 56.17 | |
| jinaai/jina-embeddings-v2-base-en: | |
| link: https://huggingface.co/jinaai/jina-embeddings-v2-base-en | |
| revision: 31b72fbf354fea65264ec54edf0b189d94b92d39 | |
| desc: jina-embeddings-v2-base-en by Jina AI | |
| seq_len: 8192 | |
| size: 137 | |
| dim: 768 | |
| license: Apache 2.0 | |
| organization: Jina AI | |
| mteb_overall: 60.38 | |
| mteb_retrieval: 47.87 | |
| mteb_sts: 80.70 | |
| mteb_clustering: 41.73 | |
| mixedbread-ai/mxbai-embed-large-v1: | |
| link: https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1 | |
| revision: 990580e27d329c7408b3741ecff85876e128e203 | |
| desc: mxbai-embed-large-v1 by mixedbread.ai | |
| seq_len: 512 | |
| size: 335 | |
| dim: 1024 | |
| license: Apache 2.0 | |
| organization: mixedbread.ai | |
| mteb_overall: 64.68 | |
| mteb_retrieval: 54.39 | |
| mteb_sts: 85.00 | |
| mteb_clustering: 46.71 | |
| nomic-ai/nomic-embed-text-v1.5: | |
| link: https://huggingface.co/nomic-ai/nomic-embed-text-v1.5 | |
| revision: b0753ae76394dd36bcfb912a46018088bca48be0 | |
| desc: nomic-embed-text-v1.5 by nomic.ai | |
| seq_len: 8192 | |
| size: 137 | |
| dim: 768 | |
| license: Apache 2.0 | |
| organization: nomic.ai | |
| mteb_overall: 62.28 | |
| mteb_retrieval: 53.01 | |
| mteb_sts: 81.94 | |
| mteb_clustering: 43.93 | |
| McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp-supervised: | |
| link: https://huggingface.co/McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp-supervised | |
| revision: baa8ebf04a1c2500e61288e7dad65e8ae42601a7 | |
| desc: LLM2Vec by McGill | |
| seq_len: 8192 | |
| size: 7505 | |
| dim: 4096 | |
| license: MIT | |
| organization: McGill | |
| mteb_overall: 65.01 | |
| mteb_retrieval: 56.63 | |
| mteb_sts: 83.58 | |
| mteb_clustering: 46.45 | |
| voyage-multilingual-2: | |
| link: https://docs.voyageai.com/docs/embeddings | |
| revision: "1" | |
| desc: voyage-multilingual-2 by Voyage AI | |
| seq_len: 32000 | |
| dim: 1024 | |
| license: Proprietary | |
| organization: Voyage AI | |
| voyage-large-2-instruct: | |
| link: https://docs.voyageai.com/docs/embeddings | |
| revision: "1" | |
| desc: voyage-large-2-instruct by Voyage AI | |
| seq_len: 16000 | |
| dim: 1024 | |
| license: Proprietary | |
| organization: Voyage AI | |
| mteb_overall: 68.28 | |
| mteb_retrieval: 58.28 | |
| mteb_sts: 84.58 | |
| mteb_clustering: 53.35 | |
| text-embedding-004: | |
| link: https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/text-embeddings-api | |
| revision: "1" | |
| desc: text-embedding-004 by Google | |
| seq_len: 2048 | |
| dim: 768 | |
| license: Proprietary | |
| organization: Google | |
| mteb_overall: 66.31 | |
| mteb_retrieval: 55.7 | |
| mteb_sts: 85.07 | |
| mteb_clustering: 47.48 | |
| text-embedding-3-large: | |
| link: https://platform.openai.com/docs/guides/embeddings | |
| revision: "1" | |
| desc: text-embedding-3-large by OpenAI | |
| seq_len: 8191 | |
| dim: 3072 | |
| license: Proprietary | |
| organization: OpenAI | |
| mteb_overall: 64.59 | |
| mteb_retrieval: 55.44 | |
| mteb_sts: 81.73 | |
| mteb_clustering: 49.01 | |
| embed-english-v3.0: | |
| link: https://docs.cohere.com/docs/cohere-embed | |
| revision: "1" | |
| desc: embed-english-v3.0 by Cohere | |
| seq_len: 512 | |
| dim: 1024 | |
| license: Proprietary | |
| organization: Cohere | |
| mteb_overall: 64.47 | |
| mteb_retrieval: 55 | |
| mteb_sts: 82.62 | |
| mteb_clustering: 47.43 | |
| BM25: | |
| link: https://github.com/xhluca/bm25s | |
| desc: Fast lexical search via BM25 | |
| license: MIT | |
| mteb_retrieval: 42.4 | |