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Path: /vector/features/embeddingmodels
[mixedbread-ai/mxbai-embed-large-v1](https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1) 1024 512 64.68 [WhereIsAI/UAE-Large-V1](https://huggingface.co/WhereIsAI/UAE-Large-V1) 1024 512 64.64 [BAAI/bge-large-en-v1.5](https://huggingface.co/BAAI/bge-large-en-v1.5) 1024 512 64.23 [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) 768 512 63.55 [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) 384 512 62.17 [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) 384 256 56.26 [BAAI/bge-m3](https://huggingface.co/BAAI/bge-m3) 1024 8192 * [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) 768 512 38.33
I'd like more long token limit options with higher performance. 8k tokens is my minimum for consideration. Something like these would be ideal:
https://huggingface.co/dunzhang/stella_en_400M_v5 https://huggingface.co/Alibaba-NLP/gte-Qwen2-1.5B-instruct
The text was updated successfully, but these errors were encountered:
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Path: /vector/features/embeddingmodels
I'd like more long token limit options with higher performance. 8k tokens is my minimum for consideration. Something like these would be ideal:
https://huggingface.co/dunzhang/stella_en_400M_v5
https://huggingface.co/Alibaba-NLP/gte-Qwen2-1.5B-instruct
The text was updated successfully, but these errors were encountered: