Update README.md

README.md

@@ -12,9 +12,15 @@ short_description: Logic Gate Learning with Neural Networks
 license: mit
 ---
 
-# Welcome to Streamlit!
+# **Embedding Dimension Visualizer**
 
-Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:
+An **Embedding Dimension Visualizer** is an interactive Streamlit tool designed for teaching and experimentation with modern transformer embeddings. It lets you:
 
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
+* **Tokenize** any input text using tiktoken or HuggingFace’s BPE tokenizer, showing each subword token and its ID.
+* **Visualize embeddings** by generating a demo embedding vector for every token.
+* **Compute and display sinusoidal positional encodings** (sin / cos) per token position.
+* **Combine embeddings + positional encodings** and present the final per-token vectors exactly as they’d be fed into attention heads.
+* **Expose theory** via an expandable section—complete with LaTeX formulas—covering tokenization, BPE, and the positional-encoding equations.
+* **Lock sliders** into read-only mode, so learners can observe values without accidentally altering them.
+
+This app is ideal for workshops, live demos, or self-study when you want a hands-on, visual understanding of how embeddings and positional information come together inside a transformer model.