From cbf98de120517fb55349593d23bb5d3f917cacb0 Mon Sep 17 00:00:00 2001 From: Sabrina Aquino <77522207+sabrinaaquino@users.noreply.github.com> Date: Wed, 21 Feb 2024 15:16:32 -0300 Subject: [PATCH] Update qdrant-landing/content/blog/binary-quantization-openai.md Co-authored-by: Mike Jang --- qdrant-landing/content/blog/binary-quantization-openai.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/qdrant-landing/content/blog/binary-quantization-openai.md b/qdrant-landing/content/blog/binary-quantization-openai.md index 7fcb61cb8..61fedb73c 100644 --- a/qdrant-landing/content/blog/binary-quantization-openai.md +++ b/qdrant-landing/content/blog/binary-quantization-openai.md @@ -32,7 +32,7 @@ In this post, we discuss: - Implications of these findings for real-world applications - Best practices for leveraging Binary Quantization to enhance OpenAI embeddings -You can also try out these techniques with the following Jupyter notebook: [OpenAI Embeddings with Qdrant's Binary Quantization](https://github.com/qdrant/examples/blob/openai-3/binary-quantization-openai/analysis/01_analysis.ipynb) +You can also try out these techniques as described in [Binary Quantization OpenAI](https://github.com/qdrant/examples/blob/openai-3/binary-quantization-openai/README.md), which includes Jupyter notebooks. ## New OpenAI Embeddings: Performance and Changes