Gemma Scope

Sparse autoencoder suite for Gemma 2 9B and 2B models.

CommonProductProgrammingautoencodersdeep learning

Gemma Scope is a set of sparse autoencoders designed for the 9B and 2B models of Gemma. It acts like a microscope, helping us analyze the internal activations of these models, thereby deepening our understanding of the concepts behind them. These autoencoders can be used to study the internal activations of the models, similar to how biologists use microscopes to examine the cells of plants and animals.

Provides analysis tools for the internal activations of the Gemma 2 model.
Supports different variants of the Gemma 2 9B and 2B models.
Offers various sparse autoencoders for analysis at different layers.
Allows users to understand how to use Gemma Scope through Google Colab notebook tutorials.
Provides technical reports and blog articles for an in-depth understanding of the product.
Collaborates with Neuronpedia to offer interactive demonstrations.
Internally uses Mishax tools to expose the internal activations of the Gemma 2 model.

\Gemma Scope is primarily aimed at data scientists
machine learning researchers
and deep learning developers who need a deep understanding of the inner workings of large language models.\

Researchers use Gemma Scope to analyze the internal structure of specific language models.
Data scientists leverage Gemma Scope to optimize model parameters and enhance performance.
Developers utilize Gemma Scope to understand the decision-making process of models and improve their interpretability.

Visit the Hugging Face website and search for the Gemma Scope model.
Choose a suitable variant of the Gemma 2 model
such as 2B or 9B.
Read technical reports and blog articles to understand how Gemma Scope operates.
Learn how to use Gemma Scope through Google Colab notebook tutorials.

Visit

Gemma Scope Visit Over Time

Monthly Visits

21315886

Bounce Rate

45.50%

Page per Visit

5.2

Visit Duration

00:05:02

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