Update tutorial section of readme.md

README.md

@@ -13,13 +13,12 @@
   - [About MACE](#about-mace)
   - [Documentation](#documentation)
   - [Installation](#installation)
-    - [pip installation](#pip-installation)
-    - [conda installation](#conda-installation)
-    - [pip installation from source](#pip-installation-from-source)
+    - [pip installation](#installation-from-pypi)
+    - [pip installation from source](#installation-from-source)
   - [Usage](#usage)
     - [Training](#training)
     - [Evaluation](#evaluation)
-  - [Tutorial](#tutorial)
+  - [Tutorials](#tutorials)
   - [Weights and Biases for experiment tracking](#weights-and-biases-for-experiment-tracking)
   - [Pretrained Foundation Models](#pretrained-foundation-models)
     - [MACE-MP: Materials Project Force Fields](#mace-mp-materials-project-force-fields)
@@ -57,7 +56,7 @@ A partial documentation is available at: https://mace-docs.readthedocs.io
 
 **Make sure to install PyTorch.** Please refer to the [official PyTorch installation](https://pytorch.org/get-started/locally/) for the installation instructions. Select the appropriate options for your system.
 
-### 2a. Installation from PyPI
+### Installation from PyPI
 This is the recommended way to install MACE. 
 
 ```sh
@@ -67,7 +66,7 @@ pip install mace-torch
 **Note:** The homonymous package on [PyPI](https://pypi.org/project/MACE/) has nothing to do with this one.
 
 
-### 2b. Installation from source
+### Installation from source
 
 
 ```sh
@@ -162,11 +161,15 @@ mace_eval_configs \
     --output="./your_output.xyz"
 ```
 
-## Tutorial
+## Tutorials
 
 You can run our [Colab tutorial](https://colab.research.google.com/drive/1D6EtMUjQPey_GkuxUAbPgld6_9ibIa-V?authuser=1#scrollTo=Z10787RE1N8T) to quickly get started with MACE.
 
-We also have a more detailed user and developer tutorial at https://github.com/ilyes319/mace-tutorials
+We also have a more detailed Colab tutorials on:
+ - [Introduction to MACE training and evaluation](https://colab.research.google.com/drive/1ZrTuTvavXiCxTFyjBV4GqlARxgFwYAtX)
+ - [Introduction to MACE active learning and fine-tuning](https://colab.research.google.com/drive/1oCSVfMhWrqHTeHbKgUSQN9hTKxLzoNyb)
+ - [MACE theory and code (advanced)](https://colab.research.google.com/drive/1AlfjQETV_jZ0JQnV5M3FGwAM2SGCl2aU)
+
 
 ## On-line data loading for large datasets