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title: EvoTransformer V2.1 | |
emoji: π₯ | |
colorFrom: pink | |
colorTo: blue | |
sdk: gradio | |
sdk_version: 5.36.2 | |
app_file: app.py | |
pinned: false | |
license: apache-2.0 | |
''' | |
# EvoTransformer v2.1 π§ β¨ | |
EvoTransformer is an evolving neural architecture built from scratch to tackle reasoning tasks with minimal compute. | |
## π What It Does | |
This model answers PIQA-style commonsense reasoning questions. Given a goal and two solution choices, EvoTransformer chooses the more logical one. | |
## π§ Architecture | |
- Built with 4 Transformer encoder layers | |
- ~13 million parameters | |
- Custom embedding, pooling, and classifier layers | |
- Fully open and adaptable for NAS or self-evolving tasks | |
## ποΈββοΈ Training Details | |
- Dataset: PIQA (1000 training, 500 validation examples) | |
- Optimizer: Adam | |
- Loss: CrossEntropy | |
- Epochs: 5 | |
- Hardware: Colab GPU | |
## π Live Demo | |
Try it on Hugging Face Spaces: | |
π [Demo Link](https://huggingface.co/spaces/YOUR_USERNAME/evo-transformer-demo) | |
## π‘ Why EvoTransformer? | |
- Lean, fast, and efficient | |
- Custom-built from scratch (no pretraining dependencies) | |
- Can evolve structurally in future versions | |
## π License | |
MIT | |
''' | |