Merge pull request #25 from refuel-ai/broken-links

Minor update

docs/autolabel/guide/overview/getting-started.md

@@ -28,7 +28,7 @@ Let's say we wanted to run sentiment analysis on a dataset of movie reviews. We
 
 Now, we could label a few hundred examples by hand which would take us a few hours. Instead, let's use Autolabel to get a clean, labeled dataset in a few minutes.
 
-A dataset[^1] containing 200 unlabeled movie reviews is available [here](https://github.com/refuel-ai/autolabel/blob/main/docs/assets/movie_reviews_preview.csv), and a couple of examples (with labels) are shown below:
+A dataset[^1] containing 200 unlabeled movie reviews is available [here](https://github.com/refuel-ai/autolabel/blob/main/docs/assets/movie_reviews.csv), and a couple of examples (with labels) are shown below:
 
 {{ read_csv('docs/assets/movie_reviews_preview.csv') }}
 
@@ -89,7 +89,7 @@ config = {
 }
 ```
 
-*To create a custom configuration, you can use the [CLI](https://docs.refuel.ai/guide/resources/CLI) or [write your own](https://docs.refuel.ai/guide/resources/configs/).*
+*To create a custom configuration, you can use the [CLI](../resources/CLI.md) or [write your own](../resources/configs.md).*
 
 ### Preview the labeling against your dataset
 

docs/autolabel/guide/overview/tutorial-classification.md

@@ -23,9 +23,9 @@ get_data('civil_comments')
 
 The output is:
 ```
-Downloading seed example dataset to "seed.csv"...
+Downloading seed example dataset to "data/civil-comments/seed.csv"...
 100% [..............................................................................] 65757 / 65757
-Downloading test dataset to "test.csv"...
+Downloading test dataset to "data/civil-comments/test.csv"...
 100% [............................................................................] 610663 / 610663
 ```
 
@@ -73,14 +73,14 @@ config = {
     }
 }
 ```
-*To create a custom configuration, you can use the [CLI](https://docs.refuel.ai/guide/resources/CLI) or [write your own](https://docs.refuel.ai/guide/resources/configs).*
+*To create a custom configuration, you can use the [CLI](../resources/CLI.md) or [write your own](../resources/configs.md).*
 
 Now, we do the dry-run with `agent.plan`:
 ```python
 from autolabel import LabelingAgent, AutolabelDataset
 
 agent = LabelingAgent(config)
-ds = AutolabelDataset('test.csv', config = config)
+ds = AutolabelDataset('data/civil-comments/test.csv', config = config)
 agent.plan(ds)
 ```
 

docs/autolabel/guide/resources/refuel_datasets.md

@@ -5,6 +5,7 @@ Autolabel provides datasets out-of-the-box so you can easily get started with LL
 | banking        | Classification        |
 | civil_comments | Classification        |
 | ledgar         | Classification        |
+| movie_reviews  | Classification        |
 | walmart_amazon | Entity Matching       |
 | company        | Entity Matching       |
 | squad_v2       | Question Answering    |
@@ -14,14 +15,14 @@ Autolabel provides datasets out-of-the-box so you can easily get started with LL
 
 ## Downloading any dataset
 
-To download a specific dataset, such as `squad_v2`, run:
+To download a specific dataset, such as `civil_comments`, run:
 ```python
 from autolabel import get_data
 
 get_data('civil_comments')
-> Downloading seed example dataset to "seed.csv"...
+> Downloading seed example dataset to "data/civil_comments/seed.csv"...
 > 100% [..............................................................................] 65757 / 65757
 
-> Downloading test dataset to "test.csv"...
+> Downloading test dataset to "data/civil_comments/test.csv"...
 > 100% [............................................................................] 610663 / 610663
 ```