core: Convert SimSIMD back to NumPy #19473
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gkorland
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Mar 30, 2024
This patch fixes the langchain-ai#18022 issue, converting the SimSIMD internal zero-copy outputs to NumPy. I've also noticed, that oftentimes `dtype=np.float32` conversion is used before passing to SimSIMD. Which numeric types do LangChain users generally care about? We support `float64`, `float32`, `float16`, and `int8` for cosine distances and `float16` seems reasonable for practically any kind of embeddings and any modern piece of hardware, so we can change that part as well 🤗
chrispy-snps
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Mar 30, 2024
This patch fixes the langchain-ai#18022 issue, converting the SimSIMD internal zero-copy outputs to NumPy. I've also noticed, that oftentimes `dtype=np.float32` conversion is used before passing to SimSIMD. Which numeric types do LangChain users generally care about? We support `float64`, `float32`, `float16`, and `int8` for cosine distances and `float16` seems reasonable for practically any kind of embeddings and any modern piece of hardware, so we can change that part as well 🤗
hinthornw
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Apr 26, 2024
This patch fixes the #18022 issue, converting the SimSIMD internal zero-copy outputs to NumPy. I've also noticed, that oftentimes `dtype=np.float32` conversion is used before passing to SimSIMD. Which numeric types do LangChain users generally care about? We support `float64`, `float32`, `float16`, and `int8` for cosine distances and `float16` seems reasonable for practically any kind of embeddings and any modern piece of hardware, so we can change that part as well 🤗
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This patch fixes the #18022 issue, converting the SimSIMD internal zero-copy outputs to NumPy.
I've also noticed, that oftentimes
dtype=np.float32conversion is used before passing to SimSIMD. Which numeric types do LangChain users generally care about? We supportfloat64,float32,float16, andint8for cosine distances andfloat16seems reasonable for practically any kind of embeddings and any modern piece of hardware, so we can change that part as well 🤗