From 2ca6e83dcfb716bfbe01a88b8187cfeddc105c30 Mon Sep 17 00:00:00 2001 From: mrmer1 Date: Thu, 2 Jan 2025 17:05:24 +0800 Subject: [PATCH] update colab links --- .../build-things-with-cohere/building-a-chatbot-with-cohere.mdx | 2 +- .../build-things-with-cohere/building-an-agent-with-cohere.mdx | 2 +- .../v2/tutorials/build-things-with-cohere/rag-with-cohere.mdx | 2 +- .../build-things-with-cohere/reranking-with-cohere.mdx | 2 +- .../build-things-with-cohere/semantic-search-with-cohere.mdx | 2 +- .../build-things-with-cohere/text-generation-tutorial.mdx | 2 +- 6 files changed, 6 insertions(+), 6 deletions(-) diff --git a/fern/pages/v2/tutorials/build-things-with-cohere/building-a-chatbot-with-cohere.mdx b/fern/pages/v2/tutorials/build-things-with-cohere/building-a-chatbot-with-cohere.mdx index f1395606..3d6f6011 100644 --- a/fern/pages/v2/tutorials/build-things-with-cohere/building-a-chatbot-with-cohere.mdx +++ b/fern/pages/v2/tutorials/build-things-with-cohere/building-a-chatbot-with-cohere.mdx @@ -7,7 +7,7 @@ image: "../../../../assets/images/f1cc130-cohere_meta_image.jpg" keywords: "Cohere, chatbot" --- -Open in Colab +Open in Colab As its name implies, the Chat endpoint enables developers to build chatbots that can handle conversations. At the core of a conversation is a multi-turn dialog between the user and the chatbot. This requires the chatbot to have the state (or “memory”) of all the previous turns to maintain the state of the conversation. diff --git a/fern/pages/v2/tutorials/build-things-with-cohere/building-an-agent-with-cohere.mdx b/fern/pages/v2/tutorials/build-things-with-cohere/building-an-agent-with-cohere.mdx index bea4a443..a9f65da7 100644 --- a/fern/pages/v2/tutorials/build-things-with-cohere/building-an-agent-with-cohere.mdx +++ b/fern/pages/v2/tutorials/build-things-with-cohere/building-an-agent-with-cohere.mdx @@ -7,7 +7,7 @@ image: "../../../../assets/images/f1cc130-cohere_meta_image.jpg" keywords: "Cohere, agents" --- -Open in Colab +Open in Colab Tool use extends the ideas from [RAG](/v2/docs/rag-with-cohere), where external systems are used to guide the response of an LLM, but by leveraging a much bigger set of tools than what’s possible with RAG. The concept of tool use leverages LLMs' useful feature of being able to act as a reasoning and decision-making engine. diff --git a/fern/pages/v2/tutorials/build-things-with-cohere/rag-with-cohere.mdx b/fern/pages/v2/tutorials/build-things-with-cohere/rag-with-cohere.mdx index dde08b8b..1db00b8a 100644 --- a/fern/pages/v2/tutorials/build-things-with-cohere/rag-with-cohere.mdx +++ b/fern/pages/v2/tutorials/build-things-with-cohere/rag-with-cohere.mdx @@ -7,7 +7,7 @@ image: "../../../../assets/images/f1cc130-cohere_meta_image.jpg" keywords: "Cohere, retrieval-augmented generation, RAG" --- -Open in Colab +Open in Colab The Chat endpoint provides comprehensive support for various text generation use cases, including retrieval-augmented generation (RAG). diff --git a/fern/pages/v2/tutorials/build-things-with-cohere/reranking-with-cohere.mdx b/fern/pages/v2/tutorials/build-things-with-cohere/reranking-with-cohere.mdx index ed9def61..2e603524 100644 --- a/fern/pages/v2/tutorials/build-things-with-cohere/reranking-with-cohere.mdx +++ b/fern/pages/v2/tutorials/build-things-with-cohere/reranking-with-cohere.mdx @@ -7,7 +7,7 @@ image: "../../../../assets/images/f1cc130-cohere_meta_image.jpg" keywords: "Cohere, language models, ReRank models" --- -Open in Colab +Open in Colab Reranking is a technique that leverages [embeddings](/v2/docs/embeddings) as the last stage of a retrieval process, and is especially useful in [RAG systems](/v2/docs/retrieval-augmented-generation-rag). diff --git a/fern/pages/v2/tutorials/build-things-with-cohere/semantic-search-with-cohere.mdx b/fern/pages/v2/tutorials/build-things-with-cohere/semantic-search-with-cohere.mdx index 945e20f2..b2f16837 100644 --- a/fern/pages/v2/tutorials/build-things-with-cohere/semantic-search-with-cohere.mdx +++ b/fern/pages/v2/tutorials/build-things-with-cohere/semantic-search-with-cohere.mdx @@ -7,7 +7,7 @@ image: "../../../../assets/images/f1cc130-cohere_meta_image.jpg" keywords: "Cohere, language models, " --- -Open in Colab +Open in Colab [Text embeddings](/v2/docs/embeddings) are lists of numbers that represent the context or meaning inside a piece of text. This is particularly useful in search or information retrieval applications. With text embeddings, this is called semantic search. diff --git a/fern/pages/v2/tutorials/build-things-with-cohere/text-generation-tutorial.mdx b/fern/pages/v2/tutorials/build-things-with-cohere/text-generation-tutorial.mdx index 5575adb9..cb4483a8 100644 --- a/fern/pages/v2/tutorials/build-things-with-cohere/text-generation-tutorial.mdx +++ b/fern/pages/v2/tutorials/build-things-with-cohere/text-generation-tutorial.mdx @@ -7,7 +7,7 @@ image: "../../../../assets/images/f1cc130-cohere_meta_image.jpg" keywords: "Cohere, how do LLMs generate text" --- -Open in Colab +Open in Colab Command is Cohere’s flagship LLM. It generates a response based on a user message or prompt. It is trained to follow user commands and to be instantly useful in practical business applications, like summarization, copywriting, extraction, and question-answering.