diff --git a/README.md b/README.md
index cff1adbc..06b3d32d 100644
--- a/README.md
+++ b/README.md
@@ -11,7 +11,7 @@ The current Python versions supported are 3.9, 3.10, 3.11.
 ## Initial Setup
 First clone the repository:
 ```bash
-git clone git@github.com:IBM/tsfm.git
+git clone git@github.com:ibm-granite/granite-tsfm.git
 cd tsfm
 ```
 
@@ -24,9 +24,9 @@ pip install ".[notebooks]"
 ```
 
 ### Notebooks links
-- Getting started with `PatchTSMixer` [[Try it out]](https://github.com/IBM/tsfm/blob/main/notebooks/hfdemo/patch_tsmixer_getting_started.ipynb)
-- Transfer learning with `PatchTSMixer` [[Try it out]](https://github.com/IBM/tsfm/blob/main/notebooks/hfdemo/patch_tsmixer_transfer.ipynb)
-- Transfer learning with `PatchTST` [[Try it out]](https://github.com/IBM/tsfm/blob/main/notebooks/hfdemo/patch_tst_transfer.ipynb)
+- Getting started with `PatchTSMixer` [[Try it out]](https://github.com/ibm-granite/granite-tsfm/blob/main/notebooks/hfdemo/patch_tsmixer_getting_started.ipynb)
+- Transfer learning with `PatchTSMixer` [[Try it out]](https://github.com/ibm-granite/granite-tsfm/blob/main/notebooks/hfdemo/patch_tsmixer_transfer.ipynb)
+- Transfer learning with `PatchTST` [[Try it out]](https://github.com/ibm-granite/granite-tsfm/blob/main/notebooks/hfdemo/patch_tst_transfer.ipynb)
 - Getting started with `TinyTimeMixer (TTM)` [Try it out](notebooks/hfdemo/ttm_getting_started.ipynb)
 
 ## 📗 Google Colab
@@ -40,14 +40,12 @@ The demo presented at NeurIPS 2023 is available in `tsfmhfdemos`. This demo requ
 pip install ".[demos]"
 ```
 
-
 ## Issues
-If you encounter an issue with this project, you are welcome to submit a [bug report](https://github.com/IBM/TSFM/issues).
+If you encounter an issue with this project, you are welcome to submit a [bug report](https://github.com/ibm-granite/granite-tsfm/issues).
 Before opening a new issue, please search for similar issues. It's possible that someone has already reported it.
 
 
 # Notice
-
 The intention of this repository is to make it easier to use and demonstrate IBM Research TSFM components that have been made available in the [Hugging Face transformers library](https://huggingface.co/docs/transformers/main/en/index). As we continue to develop these capabilities we will update the code here.