Add model card and metadata

README.md

@@ -1 +1,28 @@
-arxiv.org/abs/2603.27027
+---
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+# TAPS: Task-Aware Proposal Distributions for Speculative Sampling
+
+This model is a lightweight drafter introduced in the paper [TAPS: Task Aware Proposal Distributions for Speculative Sampling](https://huggingface.co/papers/2603.27027).
+
+## Overview
+TAPS (Task-Aware Proposal Distributions for Speculative Sampling) studies how the draft training distribution shapes speculative decoding quality. Using specialist drafters (like HASS and EAGLE-2), the work demonstrates that speculative decoding performance depends significantly on the match between draft training data and downstream workloads.
+
+This repository contains a lightweight LLaMA-style drafter designed to be used in conjunction with a larger verifier model (such as Meta-Llama-3-8B-Instruct) to accelerate autoregressive generation.
+
+## Resources
+- **Paper**: [TAPS: Task Aware Proposal Distributions for Speculative Sampling](https://huggingface.co/papers/2603.27027)
+- **GitHub Repository**: [Moe-Zbeeb/TAPS](https://github.com/Moe-Zbeeb/TAPS)
+
+## Citation
+```bibtex
+@article{zbib2026taps,
+  title={TAPS: Task Aware Proposal Distributions for Speculative Sampling},
+  author={Zbib, Mohamad and Bazzi, Mohamad and Mohanna, Ammar and Ghanem, Bernard and Hammoud, Hasan Abed Al Kader},
+  year={2026},
+  note={Technical report}
+}
+```