README.md

metadata

title: DictionaryLearningAndAnthropic
emoji: 📈
colorFrom: blue
colorTo: purple
sdk: streamlit
sdk_version: 1.35.0
app_file: app.py
pinned: false
license: mit

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Inspired by this video which discusses how Anthropic is studying how their model works using Dictionary Learning. https://youtu.be/AYTYk-kmXuI?t=168

Importing Libraries:

streamlit for creating the app. Scikit-learn (sklearn.decomposition.DictionaryLearning and datasets.load_digits) for dictionary learning and loading the dataset. matplotlib for plotting. numpy for numerical operations. Streamlit App Initialization:

The app sets a title and a description with st.title and st.write. Loading Data:

Digit data is loaded using load_digits(). This dataset contains 8x8 images of digits (0-9). Sample Image Display:

A slider is created with st.slider to select an index for displaying a sample image from the dataset using st.image. Selecting Number of Components:

Another slider allows users to choose the number of dictionary components (n_components) for dictionary learning. Performing Dictionary Learning:

DictionaryLearning is initialized with the selected number of components and fitted to the data. The dictionary elements learned are stored in dictionary. Displaying Dictionary Components:

The learned dictionary components are displayed as images using Matplotlib. Each component is reshaped into an 8x8 image. Displaying Sparsity:

Sparsity is calculated as the mean of zero entries in the transformed data (X_transformed) and displayed with st.write.

Assistant: Sure! The requirements.txt file is used to specify the dependencies needed for your Python project. For the Streamlit application demonstrating dictionary learning, you'll need the following libraries:

streamlit to create the interactive web app. scikit-learn for performing dictionary learning and loading the dataset. matplotlib for plotting the images. numpy for numerical operations. Here is a requirements.txt file that includes all these dependencies:

streamlit>=1.0.0 scikit-learn>=0.24.0 matplotlib>=3.0.0 numpy>=1.19.0