Create README.md

README.md

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+---
+license: apache-2.0
+datasets:
+- pico-lm/pretokenized-paloma
+language:
+- en
+metrics:
+- pico-lm/perplexity
+pipeline_tag: text-generation
+---
+
+# Pico Decoder Medium
+
+**pico-decoder-medium** is a 181M parameter model in the `pico-decoder` suite, balancing scale and analyzability. Built with [`pico-train`](https://github.com/pico-lm) and instrumented with [`pico-analyze`](https://github.com/pico-lm), it enables detailed studies of layer-wise learning behavior during language model pretraining.
+
+## 🔧 Model Details
+
+| Field               | Value                              |
+|---------------------|------------------------------------|
+| **Architecture**     | Decoder-only transformer (LLaMA-style) |
+| **Parameters**       | 181M                              |
+| **Layers**           | 12                                |
+| **Hidden Size**      | 768                               |
+| **Feed Forward Size**| 3072                              |
+| **Attention Heads**  | 12                                 |
+| **Key/Value Heads**  | 4                                 |
+
+## 📚 Training
+
+- **Dataset**: [`pretokenized-dolma`](https://github.com/pico-lm)
+- **Training steps**: 200,000
+- **Batch size**: 1024
+- **Sequence length**: 2048
+- **Optimizer**: AdamW
+- **Learning rate schedule**: Linear decay with warmup
+- **Compute**: 16 A100-SXM4-80GB GPUs
+
+## 📈 Evaluation and Analysis
+
+Compatible with [`pico-analyze`](https://github.com/pico-lm) for introspecting:
+
+- Per-head loss and gradient stats
+- Learning saturation across layers
+- Token-level memorization dynamics
+
+Evaluated on [`pico-paloma-tinsy`](https://huggingface.co/datasets/pico-lm/pretokenized-paloma-tinsy) using perplexity.
+
+## 📄 Citation
+
+```bibtex
+@software{pico2025,
+    author = {Diehl Martinez, Richard},
+    title = {Pico: A Lightweight Framework for Studying Language Model Learning Dynamics},
+    year = {2025},
+    url = {https://github.com/pico-lm}
+}