From 7c66b8cb81f9e91227e488822f005e5fc0632a7f Mon Sep 17 00:00:00 2001 From: Jael Gu Date: Wed, 18 Sep 2024 12:15:35 +0800 Subject: [PATCH] Add more resources Signed-off-by: Jael Gu --- README.md | 14 ++++++++++++++ 1 file changed, 14 insertions(+) diff --git a/README.md b/README.md index 2df41f3..7732b3c 100644 --- a/README.md +++ b/README.md @@ -96,3 +96,17 @@ An image-text embedding operator takes a [towhee image](link/to/towhee/image/api + + + # More Resources + + - [The guide to instructor-xl | HKU NLP](https://zilliz.com/ai-models/instructor-xl): instructor-xl: an instruction-finetuned model tailored for text embeddings with the best performance when compared to `instructor-base` and `instructor-large.` +- [The guide to text-embedding-ada-002 model | OpenAI](https://zilliz.com/ai-models/text-embedding-ada-002): text-embedding-ada-002: OpenAI's legacy text embedding model; average price/performance compared to text-embedding-3-large and text-embedding-3-small. +- [The guide to mistral-embed | Mistral AI](https://zilliz.com/ai-models/mistral-embed): mistral-embed: a specialized embedding model for text data with a context window of 8,000 tokens. Optimized for similarity retrieval and RAG applications. +- [Supercharged Semantic Similarity Search in Production - Zilliz blog](https://zilliz.com/learn/supercharged-semantic-similarity-search-in-production): Building a Blazing Fast, Highly Scalable Text-to-Image Search with CLIP embeddings and Milvus, the most advanced open-source vector database. +- [The guide to clip-vit-base-patch32 | OpenAI](https://zilliz.com/ai-models/clip-vit-base-patch32): clip-vit-base-patch32: a CLIP multimodal model variant by OpenAI for image and text embedding. +- [The guide to all-MiniLM-L12-v2 | Hugging Face](https://zilliz.com/ai-models/all-MiniLM-L12-v2): all-MiniLM-L12-v2: a text embedding model ideal for semantic search and RAG and fine-tuned based on Microsoft/MiniLM-L12-H384-uncased +- [Sparse and Dense Embeddings: A Guide for Effective Information Retrieval with Milvus | Zilliz Webinar](https://zilliz.com/event/sparse-and-dense-embeddings-webinar): Zilliz webinar covering what sparse and dense embeddings are and when you'd want to use one over the other. +- [Image Embeddings for Enhanced Image Search - Zilliz blog](https://zilliz.com/learn/image-embeddings-for-enhanced-image-search): Image Embeddings are the core of modern computer vision algorithms. Understand their implementation and use cases and explore different image embedding models. +- [Sparse and Dense Embeddings: A Guide for Effective Information Retrieval with Milvus | Zilliz Webinar](https://zilliz.com/event/sparse-and-dense-embeddings-webinar/success): Zilliz webinar covering what sparse and dense embeddings are and when you'd want to use one over the other. + \ No newline at end of file