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 Tiny
+
+**pico-decoder-tiny** is the smallest (11M) model in the `pico-decoder` suite — a lightweight, LLaMA-style decoder-only transformer trained from scratch using [`pico-train`](https://github.com/pico-lm/pico-train). It is designed for transparent and reproducible research into the learning dynamics of language models, and is fully compatible with the `pico-analyze` toolkit for detailed interpretability analysis.
+
+## 🔧 Model Details
+
+| Field               | Value                              |
+|---------------------|------------------------------------|
+| **Architecture**     | Decoder-only transformer (LLaMA-style) |
+| **Parameters**       | 11M                               |
+| **Layers**           | 12                                |
+| **Hidden Size**      | 96                               |
+| **Feed Foward Size** | 384                                |
+| **Attention Heads**  | 12                                 |
+| **Key/Value Heads**  | 4                                  |
+
+## 📚 Training
+
+- **Dataset**: [`pretokenized-dolma`](https://huggingface.co/datasets/pico-lm/pretokenized-dolma), English-only
+- **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
+
+This model supports fine-grained analysis using [`pico-analyze`](https://github.com/pico-lm/pico-analyze). This tool enables researchers to understand how learning unfolds over training, even at very small scales.
+
+We also evaluate perplexity of the model on the [`pico-paloma-tinsy`](https://huggingface.co/datasets/pico-lm/pretokenized-paloma-tinsy) dataset.
+
+## 📄 Citation
+
+If you use `pico-tiny` or any other `pico-decoder` model in your research, please cite:
+
+```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}
+}
+```