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  1. README.md +4 -2
README.md CHANGED
@@ -29,7 +29,7 @@ This is a landing page for **Gemma Scope**, a comprehensive, open suite of spars
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  - Check out the [interactive Gemma Scope demo](https://www.neuronpedia.org/gemma-scope) made by [Neuronpedia](https://www.neuronpedia.org/).
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  - 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).
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  - Check out our [Google Colab notebook tutorial](https://colab.research.google.com/drive/17dQFYUYnuKnP6OwQPH9v_GSYUW5aj-Rp?ts=66a77041) for how to use Gemma Scope.
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- - Read [the Gemma Scope technical report](https://storage.googleapis.com/gemma-scope/gemma-scope-report.pdf).
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  - 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.
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  # Full weight set:
@@ -38,7 +38,7 @@ The full list of SAEs we trained at which sites and layers are linked from the f
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  | <big>Gemma 2 Model</big> | <big>SAE Width</big> | <big>Attention</big> | <big>MLP</big> | <big>Residual</big> | <big>Tokens</big> |
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  |---------------|-----------|-----------|-----|----------|----------|
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- | 2.6B PT<br>(26 layers) | 2^14 ≈ 16.4K | [All](https://huggingface.co/google/gemma-scope-2b-pt-att) | [All](https://huggingface.co/google/gemma-scope-2b-pt-mlp) | [All](https://huggingface.co/google/gemma-scope-2b-pt-res) | 4B |
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  | | 2^15 | | | {[12](https://huggingface.co/google/gemma-scope-2b-pt-res/tree/main/layer_12/width_32k/)} | 8B |
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  | | 2^16 | [All](https://huggingface.co/google/gemma-scope-2b-pt-att) | [All](https://huggingface.co/google/gemma-scope-2b-pt-mlp) | [All](https://huggingface.co/google/gemma-scope-2b-pt-res) | 8B |
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  | | 2^17 | | | {[12](https://huggingface.co/google/gemma-scope-2b-pt-res/tree/main/layer_12/width_131k/)} | 8B |
@@ -53,6 +53,8 @@ The full list of SAEs we trained at which sites and layers are linked from the f
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  | | 2^19 | | | {[20](https://huggingface.co/google/gemma-scope-9b-pt-res/tree/main/layer_20/width_524k/)} | 8B |
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  | | 2^20 | | | {[9](https://huggingface.co/google/gemma-scope-9b-pt-res/tree/main/layer_9/width_1m/), [20](https://huggingface.co/google/gemma-scope-9b-pt-res/tree/main/layer_20/width_1m/), [31](https://huggingface.co/google/gemma-scope-9b-pt-res/tree/main/layer_31/width_1m/)} | 16B |
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  | 27B PT<br>(46 layers) | 2^17 | | | {[10](https://huggingface.co/google/gemma-scope-27b-pt-res/tree/main/layer_10/width_131k/), [22](https://huggingface.co/google/gemma-scope-27b-pt-res/tree/main/layer_22/width_131k/), [34](https://huggingface.co/google/gemma-scope-27b-pt-res/tree/main/layer_34/width_131k/)} | 8B |
 
 
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  # Which SAE is in the [Neuronpedia demo](https://www.neuronpedia.org/gemma-scope)?
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  - Check out the [interactive Gemma Scope demo](https://www.neuronpedia.org/gemma-scope) made by [Neuronpedia](https://www.neuronpedia.org/).
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  - 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).
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  - Check out our [Google Colab notebook tutorial](https://colab.research.google.com/drive/17dQFYUYnuKnP6OwQPH9v_GSYUW5aj-Rp?ts=66a77041) for how to use Gemma Scope.
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+ - Read [the Gemma Scope technical report](https://arxiv.org/abs/2408.05147).
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  - 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.
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  # Full weight set:
 
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  | <big>Gemma 2 Model</big> | <big>SAE Width</big> | <big>Attention</big> | <big>MLP</big> | <big>Residual</big> | <big>Tokens</big> |
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  |---------------|-----------|-----------|-----|----------|----------|
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+ | 2.6B PT<br>(26 layers) | 2^14 ≈ 16.4K | [All](https://huggingface.co/google/gemma-scope-2b-pt-att) | [All](https://huggingface.co/google/gemma-scope-2b-pt-mlp) | [All](https://huggingface.co/google/gemma-scope-2b-pt-res)[+](https://huggingface.co/google/gemma-scope-2b-pt-transcoders) | 4B |
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  | | 2^15 | | | {[12](https://huggingface.co/google/gemma-scope-2b-pt-res/tree/main/layer_12/width_32k/)} | 8B |
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  | | 2^16 | [All](https://huggingface.co/google/gemma-scope-2b-pt-att) | [All](https://huggingface.co/google/gemma-scope-2b-pt-mlp) | [All](https://huggingface.co/google/gemma-scope-2b-pt-res) | 8B |
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  | | 2^17 | | | {[12](https://huggingface.co/google/gemma-scope-2b-pt-res/tree/main/layer_12/width_131k/)} | 8B |
 
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  | | 2^19 | | | {[20](https://huggingface.co/google/gemma-scope-9b-pt-res/tree/main/layer_20/width_524k/)} | 8B |
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  | | 2^20 | | | {[9](https://huggingface.co/google/gemma-scope-9b-pt-res/tree/main/layer_9/width_1m/), [20](https://huggingface.co/google/gemma-scope-9b-pt-res/tree/main/layer_20/width_1m/), [31](https://huggingface.co/google/gemma-scope-9b-pt-res/tree/main/layer_31/width_1m/)} | 16B |
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  | 27B PT<br>(46 layers) | 2^17 | | | {[10](https://huggingface.co/google/gemma-scope-27b-pt-res/tree/main/layer_10/width_131k/), [22](https://huggingface.co/google/gemma-scope-27b-pt-res/tree/main/layer_22/width_131k/), [34](https://huggingface.co/google/gemma-scope-27b-pt-res/tree/main/layer_34/width_131k/)} | 8B |
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+ | 9B IT<br>(42 layers) | 2^14 | | | {[9](https://huggingface.co/google/gemma-scope-9b-it-res/tree/main/layer_9/width_16k/), [20](https://huggingface.co/google/gemma-scope-9b-it-res/tree/main/layer_20/width_16k/), [31](https://huggingface.co/google/gemma-scope-9b-it-res/tree/main/layer_31/width_16k/)} | 4B |
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+ | | 2^17 | | | {[9](https://huggingface.co/google/gemma-scope-9b-it-res/tree/main/layer_9/width_131k/), [20](https://huggingface.co/google/gemma-scope-9b-it-res/tree/main/layer_20/width_131k/), [31](https://huggingface.co/google/gemma-scope-9b-it-res/tree/main/layer_31/width_131k/)} | 8B |
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  # Which SAE is in the [Neuronpedia demo](https://www.neuronpedia.org/gemma-scope)?
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