Update README.md

README.md

@@ -9,17 +9,7 @@ library_name: saelens
 
 This is a landing page for **Gemma Scope**, a comprehensive, open suite of sparse autoencoders for Gemma 2 9B and 2B. Sparse Autoencoders are a "microscope" of sorts that can help us break down a model’s internal activations into the underlying concepts, just as biologists use microscopes to study the individual cells of plants and animals.
 
-# Key links:
-
-- Learn more about Gemma Scope in our [Google DeepMind blog post](https://deepmind.google/discover/blog/gemma-scope-helping-safety-researchers-shed-light-on-the-inner-workings-of-language-models).
-- Check out the [interactive Gemma Scope demo](https://www.neuronpedia.org/gemma-scope) made by [Neuronpedia](https://www.neuronpedia.org/).
-- Check out our [Google Colab notebook tutorial](https://colab.research.google.com/drive/17dQFYUYnuKnP6OwQPH9v_GSYUW5aj-Rp?ts=66a77041) for how to use Gemma Scope.
-- Read [the Gemma Scope technical report](https://storage.googleapis.com/gemma-scope/gemma-scope-report.pdf).
-- Check out [Mishax](https://github.com/google-deepmind/mishax), a GDM internal tool that we used in this project to expose the internal activations inside Gemma 2 models.
-
-# Quick start:
-
-You can get started with Gemma Scope by downloading the weights from any of our repositories:
+**There are no model weights in this repo. If you are looking for them, please visit:**
 
 - https://huggingface.co/google/gemma-scope-2b-pt-res
 - https://huggingface.co/google/gemma-scope-2b-pt-mlp
@@ -31,6 +21,16 @@ You can get started with Gemma Scope by downloading the weights from any of our
 - https://huggingface.co/google/gemma-scope-9b-it-res
 - https://huggingface.co/google/gemma-scope-27b-pt-res
 
+# Key links:
+
+- Learn more about Gemma Scope in our [Google DeepMind blog post](https://deepmind.google/discover/blog/gemma-scope-helping-the-safety-community-shed-light-on-the-inner-workings-of-language-models).
+- Check out the [interactive Gemma Scope demo](https://www.neuronpedia.org/gemma-scope) made by [Neuronpedia](https://www.neuronpedia.org/).
+- Check out our [Google Colab notebook tutorial](https://colab.research.google.com/drive/17dQFYUYnuKnP6OwQPH9v_GSYUW5aj-Rp?ts=66a77041) for how to use Gemma Scope.
+- Read [the Gemma Scope technical report](https://storage.googleapis.com/gemma-scope/gemma-scope-report.pdf).
+- Check out [Mishax](https://github.com/google-deepmind/mishax), a GDM internal tool that we used in this project to expose the internal activations inside Gemma 2 models.
+
+# Full weight set:
+
 The full list of SAEs we trained at which sites and layers are linked from the following table, adapted from Figure 1 of our technical report:
 
 | <big>Gemma 2 Model</big> | <big>SAE Width</big> | <big>Attention</big> | <big>MLP</big> | <big>Residual</big> | <big>Tokens</big> |