fix broken links (#27)

* update broken links

* fixing broken links

fern/pages/cookbooks/analyzing-hacker-news.mdx

@@ -104,7 +104,7 @@ warnings.filterwarnings('ignore')
 pd.set_option('display.max_colwidth', None)
 ```
 
-Fill in your Cohere API key in the next cell. To do this, begin by [signing up to Cohere](https://os.cohere.ai/) (for free!) if you haven't yet. Then get your API key [here](https://dashboard.cohere.com/api-keys).
+Fill in your Cohere API key in the next cell. To do this, begin by [signing up to Cohere](https://dashboard.cohere.com/) (for free!) if you haven't yet. Then get your API key [here](https://dashboard.cohere.com/api-keys).
 
 ```python PYTHON
 co = cohere.Client("COHERE_API_KEY") # Insert your Cohere API key

fern/pages/cookbooks/basic-semantic-search.mdx

@@ -28,7 +28,7 @@ And if you're running an older version of the SDK, you might need to upgrade it
 #!pip install --upgrade cohere
 ```
 
-Get your Cohere API key by [signing up here](https://os.cohere.ai/register). Paste it in the cell below.
+Get your Cohere API key by [signing up here](https://dashboard.cohere.com/register). Paste it in the cell below.
 
 ## 1. Getting Set Up
 
@@ -50,7 +50,7 @@ warnings.filterwarnings('ignore')
 pd.set_option('display.max_colwidth', None)
 ```
 
-You'll need your API key for this next cell. [Sign up to Cohere](https://os.cohere.ai/) and get one if you haven't yet.
+You'll need your API key for this next cell. [Sign up to Cohere](https://dashboard.cohere.com/) and get one if you haven't yet.
 
 ```python PYTHON
 model_name = "embed-english-v3.0"

fern/pages/cookbooks/hello-world-meet-ai.mdx

@@ -23,7 +23,7 @@ We’ll cover three groups of tasks that you will typically work on when dealing
 - Classifying text
 - Analyzing text
 
-The first step is to install the Cohere Python SDK. Next, create an API key, which you can generate from the Cohere [dashboard](https://os.cohere.ai/register) or [CLI tool](https://docs.cohere.ai/cli-key).
+The first step is to install the Cohere Python SDK. Next, create an API key, which you can generate from the Cohere [dashboard](https://dashboard.cohere.com/register) or [CLI tool](https://docs.cohere.ai/cli-key).
 
 ```python PYTHON
 ! pip install cohere altair umap-learn -q

fern/pages/cookbooks/text-classification-using-embeddings.mdx

@@ -124,7 +124,7 @@ labels_test = labels_test[:95]
 
 ## 2. Set up the Cohere client and get the embeddings of the reviews
 
-We're now ready to retrieve the embeddings from the API. You'll need your API key for this next cell. [Sign up to Cohere](https://os.cohere.ai/) and get one if you haven't yet.
+We're now ready to retrieve the embeddings from the API. You'll need your API key for this next cell. [Sign up to Cohere](https://dashboard.cohere.com/) and get one if you haven't yet.
 
 ```python PYTHON
 model_name = "embed-english-v3.0"

fern/pages/llm-university/intro-text-generation/model-prompting.mdx

@@ -27,7 +27,7 @@ In this Chapter, we will cover the following topics regarding model prompting:
 
 Throughout the following chapters, we will cover the full spectrum of working with generative AI to enable you to build applications with it. But to start with, let’s take the no-code route: we’ll show you how AI text generation works, and how you can experiment with it in the <a target="_blank" href="https://docs.cohere.ai/docs/playground-overview?ref=txt.cohere.com&amp;__hstc=14363112.fb39cf5aec47995e64cd26603e2e04d9.1682489949734.1683512904818.1683517385804.31&amp;__hssc=14363112.109.1683517385804&amp;__hsfp=3640182760">Cohere Playground</a>.
 
-First, <a target="_blank" href="https://dashboard.cohere.ai/welcome/register?ref=txt.cohere.com&amp;__hstc=14363112.fb39cf5aec47995e64cd26603e2e04d9.1682489949734.1683512904818.1683517385804.31&amp;__hssc=14363112.109.1683517385804&amp;__hsfp=3640182760">sign up for a Cohere account</a> and then visit the <a target="_blank" href="https://os.cohere.ai/playground?ref=txt.cohere.com&amp;__hstc=14363112.fb39cf5aec47995e64cd26603e2e04d9.1682489949734.1683512904818.1683517385804.31&amp;__hssc=14363112.109.1683517385804&amp;__hsfp=3640182760">Playground</a>.
+First, <a target="_blank" href="https://dashboard.cohere.ai/welcome/register?ref=txt.cohere.com&amp;__hstc=14363112.fb39cf5aec47995e64cd26603e2e04d9.1682489949734.1683512904818.1683517385804.31&amp;__hssc=14363112.109.1683517385804&amp;__hsfp=3640182760">sign up for a Cohere account</a> and then visit the <a target="_blank" href="https://dashboard.cohere.com/playground?ref=txt.cohere.com&amp;__hstc=14363112.fb39cf5aec47995e64cd26603e2e04d9.1682489949734.1683512904818.1683517385804.31&amp;__hssc=14363112.109.1683517385804&amp;__hsfp=3640182760">Playground</a>.
 
 The Playground UI consists of a few sections. The main window is where you enter your prompt and where the output, or response, is generated. A menu of saved prompts, or _presets_, is shown in the left-hand pane, and model parameter controls are located in the right-hand pane.
 

fern/pages/llm-university/intro-text-representation/setting-up.mdx

@@ -26,7 +26,7 @@ $ pip install cohere
 
 In order to make API calls to the models, you need an API key. You can sign up for a Cohere account and create an API key, which you can generate from one of the following interfaces:
 
-- Cohere <a target="_blank" href="https://os.cohere.ai/register?ref=txt.cohere.com&amp;__hstc=14363112.fb39cf5aec47995e64cd26603e2e04d9.1682489949734.1683512904818.1683517385804.31&amp;__hssc=14363112.54.1683517385804&amp;__hsfp=3640182760">dashboard</a>
+- Cohere <a target="_blank" href="https://dashboard.cohere.com/register?ref=txt.cohere.com&amp;__hstc=14363112.fb39cf5aec47995e64cd26603e2e04d9.1682489949734.1683512904818.1683517385804.31&amp;__hssc=14363112.54.1683517385804&amp;__hsfp=3640182760">dashboard</a>
 - Cohere <a target="_blank" href="https://docs.cohere.ai/cli-key?ref=txt.cohere.com&amp;__hstc=14363112.fb39cf5aec47995e64cd26603e2e04d9.1682489949734.1683512904818.1683517385804.31&amp;__hssc=14363112.54.1683517385804&amp;__hsfp=3640182760">CLI tool</a>
 
 ### Set up the Cohere Client

fern/pages/llm-university/sandbox/chapter-1-how-to-use-coheres-endpoints-copy-copy-copy.mdx

@@ -38,7 +38,7 @@ $ pip install cohere
 
 Next, sign up for a Cohere account and create an API key, which you can generate from one of the following interfaces:
 
-- Cohere [dashboard](https://os.cohere.ai/register?ref=txt.cohere.com&__hstc=14363112.89f2baed82ac4713854553225677badd.1682345384753.1682373613982.1682437866580.5&__hssc=14363112.1.1682437866580&__hsfp=2014138109)
+- Cohere [dashboard](https://dashboard.cohere.com/register?ref=txt.cohere.com&__hstc=14363112.89f2baed82ac4713854553225677badd.1682345384753.1682373613982.1682437866580.5&__hssc=14363112.1.1682437866580&__hsfp=2014138109)
 - Cohere [CLI tool](/cli-key?ref=txt.cohere.com&__hstc=14363112.89f2baed82ac4713854553225677badd.1682345384753.1682373613982.1682437866580.5&__hssc=14363112.1.1682437866580&__hsfp=2014138109)
 
 Once that is done, you can set up the Cohere client as follows.

fern/pages/llm-university/sandbox/chapter-4-deploying-with-nextjs.mdx

@@ -55,7 +55,7 @@ Using Cohere, you can [train your system](/text-classification?ref=txt.cohere.co
 
 Cohere provides many language processing features. You’ll make use of the [classification feature](https://cohere.ai/classify?ref=txt.cohere.com&__hstc=14363112.89f2baed82ac4713854553225677badd.1682345384753.1682525878579.1682537582485.12&__hssc=14363112.3.1682537582485&__hsfp=2014138109) in this tutorial.
 
-To use Cohere, the first step is to create an account by visiting the [registration page](https://os.cohere.ai/register?ref=txt.cohere.com&__hstc=14363112.89f2baed82ac4713854553225677badd.1682345384753.1682525878579.1682537582485.12&__hssc=14363112.3.1682537582485&__hsfp=2014138109).
+To use Cohere, the first step is to create an account by visiting the [registration page](https://dashboard.cohere.com/register?ref=txt.cohere.com&__hstc=14363112.89f2baed82ac4713854553225677badd.1682345384753.1682525878579.1682537582485.12&__hssc=14363112.3.1682537582485&__hsfp=2014138109).
 
 After creating your account, you have access to a dashboard:
 
@@ -111,7 +111,7 @@ app.listen(8000)
 
 This server runs on port 8000 when Node executes this file. By using the cors and express.json methods as middleware, you can create your APIs.
 
-Next, you initialize Cohere in your application. You’ll need your API key for this, so go back to [your dashboard](https://os.cohere.ai/?ref=txt.cohere.com&__hstc=14363112.89f2baed82ac4713854553225677badd.1682345384753.1682525878579.1682537582485.12&__hssc=14363112.3.1682537582485&__hsfp=2014138109) to retrieve this key.  
+Next, you initialize Cohere in your application. You’ll need your API key for this, so go back to [your dashboard](https://dashboard.cohere.com/?ref=txt.cohere.com&__hstc=14363112.89f2baed82ac4713854553225677badd.1682345384753.1682525878579.1682537582485.12&__hssc=14363112.3.1682537582485&__hsfp=2014138109) to retrieve this key.  
 Then, create a new file in your folder called .env. In that file, paste the following:
 
 ```

fern/pages/llm-university/sandbox/chapter-5-building-a-classifier-with-the-cohere-api.mdx

@@ -251,4 +251,4 @@ And if maximizing performance is paramount, you can build a dataset and finetune
 
 Finally, if you do want to get your hands dirty with machine learning and want to decide for yourself the best classification algorithm for your task, you can go for the embeddings option.
 
-Test them out yourself [on the Cohere platform](https://os.cohere.ai/register?ref=txt.cohere.com&__hstc=14363112.89f2baed82ac4713854553225677badd.1682345384753.1682447142806.1682463578843.8&__hssc=14363112.4.1682463578843&__hsfp=2014138109).
+Test them out yourself [on the Cohere platform](https://dashboard.cohere.com/register?ref=txt.cohere.com&__hstc=14363112.89f2baed82ac4713854553225677badd.1682345384753.1682447142806.1682463578843.8&__hssc=14363112.4.1682463578843&__hsfp=2014138109).