Update README.md

README.md

@@ -45,14 +45,14 @@ configs:
   - split: test
     path: data/test-*
 ---
-# STRIDE-1
-We develop STRIDE-1 (Spatio-Temporal Road Image Dataset for Exploration), that consists of approximately 82B tokens which were arranged into a total of 6M visual "sentences" or token sequences. The sequences are generated from a relatively small set of 131k panoramic images, along with their metadata and openly available highway system data. Our approach enables a 27x increase in information, allowing for generative world model training. In essence, STRIDE-1 turns real street-view panoramic observations into a navigable, interactive environment suitable for free-play across space and time.
+# STRIDE
+We develop STRIDE (Spatio-Temporal Road Image Dataset for Exploration), that consists of approximately 82B tokens which were arranged into a total of 6M visual "sentences" or token sequences. The sequences are generated from a relatively small set of 131k panoramic images, along with their metadata and openly available highway system data. Our approach enables a 27x increase in information, allowing for generative world model training. In essence, STRIDE turns real street-view panoramic observations into a navigable, interactive environment suitable for free-play across space and time.
 
 For ease of use and data exploration, we prepared this sample of 10k detokenized paths, which amounts to about 100k projected panoramic images along with its corresponding metadata.
 
 ## Breakdown
 
-### Dataset (STRIDE-1)
+### Dataset (STRIDE)
 The full tokenized dataset is made available through two downloadable files in a public GCS bucket:
 ```bash
 gsutil -m cp gs://tera-tardis/STRIDE-1/training.jsonl . # ~327GB
@@ -62,7 +62,7 @@ gsutil -m cp gs://tera-tardis/STRIDE-1/testing.jsonl . # ~9GB
 In the future, the fully detokenized dataset will be made available. Should you need it, feel free to [contact the authors](#contacts).
 
 ### Code (TARDIS)
-The code used for training of the model is available [on GitHub](https://github.com/tera-ai/lvm_action).
+The code used for training of the model is available [on GitHub](https://github.com/tera-ai/tardis).
 
 ### Checkpoints (TARDIS)
 The checkpoint/state used for evaluation of the model was saved in MessagePack format and is made available through this downloadable file: