Reordered a few things.

fern/pages/get-started/frequently-asked-questions.mdx

@@ -33,9 +33,9 @@ Cohere’s Command models have strong performance across enterprise tasks such a
 
 </Accordion>
 
-<Accordion title="How can I use Cohere's models for various tasks and applications, such as translation, text embedding, summarization, and custom tool development?">
+<Accordion title="How can I use Cohere's models for tasks like translation, text embedding, summarization, and custom tool development?">
 
-You can access Cohere’s models through our platform (cohere.com) or through various cloud platforms including, but not limited to, Sagemaker, Bedrock, Azure AI, and OCI Generatie AI. We also have private deployments. In terms of use case specific features, please reference the latest [API documentation](https://docs.cohere.com/reference/about) to learn more about the API features and [Cookbooks](https://docs.cohere.com/page/cookbooks) with starter codes for various tasks to aid development. 
+You can access Cohere’s models through our platform (cohere.com) or through various cloud platforms including, but not limited to, Sagemaker, Bedrock, Azure AI, and OCI Generatie AI. We also have private deployments. In terms of use case specific features, please reference the latest [API documentation](https://docs.cohere.com/reference/about) to learn more about the API features and [Cookbooks](https://docs.cohere.com/page/cookbooks) with starter code for various tasks to aid development. 
 
 </Accordion>
 
@@ -62,6 +62,18 @@ Fine tuning is a powerful capability, but takes some effort to get right. You sh
 
 </Accordion>
 
+<Accordion title="What are the best practices for preparing and structuring fine-tuning data, and what are the supported file formats?">
+
+You can find the best practices for preparing and structuring fine-tuning data across these three modules. Data preparation for [chat fine-tuning](https://docs.cohere.com/docs/chat-preparing-the-data), [classify fine-tuning](https://docs.cohere.com/docs/classify-preparing-the-data) and [rerank fine-tuning](https://docs.cohere.com/docs/rerank-preparing-the-data). The primary file formats supported are jsonl and csv.
+
+</Accordion>
+
+<Accordion title="What models are available for fine-tuning using the Cohere platform?">
+
+We support fine-tuning for Command R, Command R 082024 (to be launched October 1st) on the generative side, and for Classify and Rerank models on the representation side.
+
+</Accordion>
+
 <Accordion title="What specific models are being developed by Cohere and where can I find detailed information about them?">
 
 For the latest current offerings, you should reference our [models page](https://docs.cohere.com/v1/docs/models).
@@ -76,7 +88,7 @@ This largely depends on your use case. In general, Cohere has both generative an
 
 <Accordion title="What are the capabilities of Cohere's models?">
 
-Cohere models cover a wide range of capabilities from advanced generative tasks to semantic search and other representation use cases. All of our models are multilingual and can support use cases from [RAG](https://docs.cohere.com/docs/retrieval-augmented-generation-rag) to [Tool Use](https://docs.cohere.com/docs/tools) and much more.
+Cohere models offer a wide range of capabilities, from advanced generative tasks to semantic search and other representation use cases. All of our models are multilingual and can support use cases from [RAG](https://docs.cohere.com/docs/retrieval-augmented-generation-rag) to [Tool Use](https://docs.cohere.com/docs/tools) and much more.
 
 Our [Command](https://cohere.com/command) model family is our flagship series of generative models. These models excel at taking a user instruction (or command) and generating text following the instruction. They also have conversational capabilities which means that they are well-suited for chatbots and virtual assistants.
 
@@ -127,18 +139,6 @@ You can check the range of use cases based on our customer stories [here](https:
 
 </Accordion>
 
-<Accordion title="What are the best practices for preparing and structuring fine-tuning data, and what are the supported file formats?">
-
-You can find the best practices for preparing and structuring fine-tuning data across these three modules. Data preparation for [chat fine-tuning](https://docs.cohere.com/docs/chat-preparing-the-data), [classify fine-tuning](https://docs.cohere.com/docs/classify-preparing-the-data) and [rerank fine-tuning](https://docs.cohere.com/docs/rerank-preparing-the-data). The primary file formats supported are jsonl and csv.
-
-</Accordion>
-
-<Accordion title="What models are available for fine-tuning using the Cohere platform?">
-
-We support fine-tuning for Command R, Command R 082024 (to be launched October 1st) on the generative side, and for Classify and Rerank models on the representation side.
-
-</Accordion>
-
 </AccordionGroup>
 
 ## Model Deployment
@@ -217,7 +217,7 @@ You can contact our support team at [email protected] and get help and share yo
 
 <Accordion title="How do I use the Cohere API?">
 
-The Cohere API can be accessed through the SDK and the CLI tool. We support SDKs in 4 different languages.
+The Cohere API can be accessed through the SDK and the CLI tool. We support SDKs in 4 different languages, Python, Typescript, Java, and Go.
 
 Visit the [API docs](https://docs.cohere.com/reference/about) for further details.