Updated links to colab notebook

Author: ryanemenecker

README.md

@@ -94,7 +94,7 @@ Metapredict can be used in five different ways:
 1. As a stand-alone command-line tool (installable via pip - the code in this repository).
 2. As a Python library for integrating into your favorite bioinformatics pipeline (installable via pip - the code in this repository).
 3. As a web-server for examining disorder predictions on individual sequences found at [https://metapredict.net/](https://metapredict.net/).
-4. *NEW as of August 2022:* as a Google Colab notebook for batch-predicting disorder scores for larger numbers of sequences: [**LINK HERE**](https://colab.research.google.com/github/idptools/metapredict/blob/master/colab/metapredict_colab.ipynb). Performance-wise, batch mode can predict the entire yeast proteome in ~1.5 min using the Colab Notebook and much faster if using a local GPU.
+4. *NEW as of August 2022:* as a Google Colab notebook for batch-predicting disorder scores for larger numbers of sequences: [**LINK HERE**](https://colab.research.google.com/drive/1UOrOxun9i23XDE8lFo_4I89Tw8P3Z1D-?usp=sharing). Performance-wise, batch mode can predict the entire yeast proteome in ~1.5 min using the Colab Notebook and much faster if using a local GPU.
 5. *NEW as of May 2023:* as part of the [ALBATROSS paper](https://www.nature.com/articles/s41592-023-02159-5), we provide a colab notebook for predicting IDRs on a proteome-wide scale [**LINK HERE**](https://colab.research.google.com/github/holehouse-lab/ALBATROSS-colab/blob/main/idrome_constructor/idrome_constructor.ipynb).
 
 ## How to cite

docs/getting_started.rst

@@ -8,7 +8,7 @@ What is metapredict?
 
 Our goal in building **metapredict** was to develop a robust, accurate, and high-performance predictor of intrinsic disorder that is also easy to install and use. As such, **metapredict** is implemented in Python and can be installed directly via `pip` (see below).
 
-metapredict is ALSO available via a `webserver for single sequence prediction <http://https://metapredict.net>`__ and `a Google Colab notebook for batch prediction <https://colab.research.google.com/github/idptools/metapredict/blob/master/colab/metapredict_colab.ipynb>`__. However, this documentation here focuses on the Python package which provides both a set of Python library functions and a set of command-line tools.
+metapredict is ALSO available via a `webserver for single sequence prediction <http://https://metapredict.net>`__ and `a Google Colab notebook for batch prediction <https://colab.research.google.com/drive/1UOrOxun9i23XDE8lFo_4I89Tw8P3Z1D-?usp=sharing>`__. However, this documentation here focuses on the Python package which provides both a set of Python library functions and a set of command-line tools.
 
 
 Recent metapredict updates and news
@@ -145,7 +145,7 @@ How does metapredict V2 differ from V2-FF
 
 metapredict V2 and V2-FF are identical in terms of predictions and features, with the major difference being that metapredict V2-FF offers batched predictions. Batched predictions are automatically parallelized on either the CPU or GPU. In addition, we rewrote the metapredict domain decomposition algorithm in C to provide a 10-20x improvement in performance for this step.
 
-We note that V2-FF was released after CAID, so the performance reported there is the V2 network performance. Because metapredict V2-FF is implemented in a `Google Colab notebook for batch prediction <https://colab.research.google.com/github/idptools/metapredict/blob/master/colab/metapredict_colab.ipynb>`__ you don't have to take our word for it that it's fast; just upload a proteome and see for yourself! 
+We note that V2-FF was released after CAID, so the performance reported there is the V2 network performance. Because metapredict V2-FF is implemented in a `Google Colab notebook for batch prediction <https://colab.research.google.com/drive/1UOrOxun9i23XDE8lFo_4I89Tw8P3Z1D-?usp=sharing>`__ you don't have to take our word for it that it's fast; just upload a proteome and see for yourself! **Note**: The colab notebook has now been updated to V3. However, all 3 metapredict networks are available for use in the notebook!
 
 What is new as far as the disorder prediction in V3?
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^