Upload README.md with huggingface_hub

README.md

@@ -1,72 +1,4 @@
----
-title: Titans Miras Demo
-emoji: 🧠
-colorFrom: blue
-colorTo: purple
-sdk: gradio
-sdk_version: 4.44.0
-app_file: app.py
-pinned: false
----
-
-# 🧠 Titans + MIRAS: A Brain That Changes Itself While Thinking
-
-A minimal but faithful reimplementation of **Titans** (test-time learning) and **MIRAS** (associative memory framework) using open-source models on Hugging Face.
-
-## What is this?
-
-This demo showcases a neural architecture that can **learn and update its memory while generating responses** - a brain that literally changes itself while thinking!
-
-### Key Features
-
-- 🔄 **Test-time learning**: Memory updates during inference (not just training)
-- 🎯 **Retention gate**: Surprising/novel inputs are more memorable (inspired by human memory)
-- 💾 **Persistent memory**: State is saved across sessions
-- 🤖 **Fully OSS**: Uses distilgpt2 and runs entirely on Hugging Face
-
-## Architecture
-
-```
-User Input
-    ↓
-[Base LM: distilgpt2] → Hidden States (768-dim)
-    ↓
-[Key/Value Projections] → Memory Space (256-dim)
-    ↓
-[MIRAS Memory Module] ← Test-time Gradient Updates
-    ↓
-[Text Generation] → Response + Memory Stats
-```
-
-### Components
-
-1. **Base Language Model**: distilgpt2 (frozen, no training)
-2. **Projection Layers**: Map hidden states to memory space
-3. **MIRAS Memory**: Associative memory with learnable key→value mapping
-4. **Retention Gate**: Adjusts learning rate based on surprise (loss magnitude)
-5. **Memory Store**: Persists memory state to disk
-
-## How It Works
-
-1. Input text is processed through distilgpt2
-2. Last hidden state is projected to key/value pairs
-3. Memory predicts value from key
-4. Loss (prediction error) indicates surprise
-5. Higher surprise → higher retention → faster learning
-6. Memory updated via gradient descent (1e-3 base LR)
-7. Response generated and memory saved
-
-## References
-
-- **Titans**: [Learning to Memorize at Test Time](https://arxiv.org/abs/2501.00663)
-- **MIRAS**: [Framework for Associative Memory with Attentional Bias](https://arxiv.org/abs/2504.13173)
-
-## Running Locally
-
-```bash
-pip install -r requirements.txt
-python app.py
-```
-
-Built with ❤️ exploring the future of adaptive AI systems.
-
+torch
+transformers
+gradio==3.50.2
+numpy