From 38c0e8429cc2049968c09b716802831c7a1b26ce Mon Sep 17 00:00:00 2001 From: Jael Gu Date: Wed, 18 Sep 2024 13:26:01 +0800 Subject: [PATCH] Add more resources Signed-off-by: Jael Gu --- README.md | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 3d851a6..e559d9e 100644 --- a/README.md +++ b/README.md @@ -82,14 +82,15 @@ The text in string. - # More Resources - - [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. + +# More Resources + +- [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. - [Massive Text Embedding Benchmark (MTEB)](https://zilliz.com/glossary/massive-text-embedding-benchmark-(mteb)): A standardized way to evaluate text embedding models across a range of tasks and languages, leading to better text embedding models for your app - [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. - [Tutorial: Diving into Text Embedding Models | Zilliz Webinar](https://zilliz.com/event/tutorial-text-embedding-models): Register for a free webinar diving into text embedding models in a presentation and tutorial - [Tutorial: Diving into Text Embedding Models | Zilliz Webinar](https://zilliz.com/event/tutorial-text-embedding-models/success): Register for a free webinar diving into text embedding models in a presentation and tutorial - [The guide to text-embedding-3-small | OpenAI](https://zilliz.com/ai-models/text-embedding-3-small): text-embedding-3-small: OpenAI’s small text embedding model optimized for accuracy and efficiency with a lower cost. - [The guide to voyage-large-2 | Voyage AI](https://zilliz.com/ai-models/voyage-large-2): voyage-large-2: general-purpose text embedding model; optimized for retrieval quality; ideal for tasks like summarization, clustering, and classification. -- [Training Text Embeddings with Jina AI - Zilliz blog](https://zilliz.com/blog/training-text-embeddings-with-jina-ai): In a recent talk by Bo Wang, he discussed the creation of Jina text embeddings for modern vector search and RAG systems. He also shared methodologies for training embedding models that effectively encode extensive information, along with guidance o - \ No newline at end of file +- [Training Text Embeddings with Jina AI - Zilliz blog](https://zilliz.com/blog/training-text-embeddings-with-jina-ai): In a recent talk by Bo Wang, he discussed the creation of Jina text embeddings for modern vector search and RAG systems. He also shared methodologies for training embedding models that effectively encode extensive information, along with guidance o \ No newline at end of file