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Aravind Pai

aravindpai

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replied to tomaarsen's post 24 days ago

🏅 Quantized Embeddings are here! Unlike model quantization, embedding quantization is a post-processing step for embeddings that converts e.g. `float32` embeddings to binary or `int8` embeddings. This saves 32x or 4x memory & disk space, and these embeddings are much easier to compare! Our results show 25-45x speedups in retrieval compared to full-size embeddings, while keeping 96% of the performance! Learn more about it in our blogpost in collaboration with mixedbread.ai: https://huggingface.co/blog/embedding-quantization Or try out our demo where we use quantized embeddings to let you search all of Wikipedia (yes, 41,000,000 texts) in 1 second on a CPU Space: https://huggingface.co/spaces/sentence-transformers/quantized-retrieval

new activity about 1 year ago

microsoft/Phi-3-mini-128k-instruct:Irrelvant response

new activity about 1 year ago

microsoft/Phi-3-mini-128k-instruct:Irrelvant response

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New activity in microsoft/Phi-3-mini-128k-instruct about 1 year ago

Irrelvant response

#64 opened about 1 year ago by

Irrelvant response

#64 opened about 1 year ago by