From ed7110a9919d71d7df3aef1de5f04433563fa623 Mon Sep 17 00:00:00 2001 From: Jael Gu Date: Wed, 18 Sep 2024 13:33:49 +0800 Subject: [PATCH] Add more resources Signed-off-by: Jael Gu --- README.md | 13 ++++++++++++- 1 file changed, 12 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 8e923b6..1745511 100644 --- a/README.md +++ b/README.md @@ -84,4 +84,15 @@ The text in string. *numpy.ndarray* -The text embedding extracted by model. \ No newline at end of file +The text embedding extracted by model. + +# 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. +- [Sentence Transformers for Long-Form Text - Zilliz blog](https://zilliz.com/learn/Sentence-Transformers-for-Long-Form-Text): Deep diving into modern transformer-based embeddings for long-form text. +- [Building Open Source Chatbots with LangChain and Milvus in 5m - Zilliz blog](https://zilliz.com/blog/building-open-source-chatbot-using-milvus-and-langchain-in-5-minutes): A start-to-finish tutorial for RAG retrieval and question-answering chatbot on custom documents using Milvus, LangChain, and an open-source LLM. +- [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. +- [Evaluating Your Embedding Model - Zilliz blog](https://zilliz.com/learn/evaluating-your-embedding-model): Review some practical examples to evaluate different text embedding models. +- [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. \ No newline at end of file