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Add model card and metadata

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Hi! I'm Niels, part of the community science team at Hugging Face.

I've opened this PR to improve the model card for this repository. Specifically, I have:
- Added metadata to the YAML section (`pipeline_tag`, `library_name`, and `license`).
- Included a descriptive summary of the model and its role in speculative decoding as presented in the TAPS paper.
- Added links to the paper and the official GitHub repository.
- Added the BibTeX citation for the paper.

Feel free to merge this if it looks good to you!

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  1. README.md +30 -1
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- arxiv.org/abs/2603.27027
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: apache-2.0
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+ library_name: transformers
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+ pipeline_tag: text-generation
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+ ---
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+
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+ # TAPS: Task-Aware Proposal Distributions for Speculative Sampling
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+
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+ This repository contains a draft model checkpoint introduced in the paper [TAPS: Task Aware Proposal Distributions for Speculative Sampling](https://huggingface.co/papers/2603.27027).
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+
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+ ## Introduction
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+ TAPS studies how the training distribution of draft models shapes the quality and efficiency of speculative decoding. By utilizing task-specific training (e.g., on MathInstruct or ShareGPT), draft models can achieve significant acceleration on matched downstream workloads. This repository provides specialized drafters (such as HASS or EAGLE-2 variants) designed for use with larger verifier models like Meta-Llama-3-8B-Instruct.
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+
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+ ## Resources
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+ - **Paper:** [TAPS: Task Aware Proposal Distributions for Speculative Sampling](https://arxiv.org/abs/2603.27027)
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+ - **GitHub Repository:** [Moe-Zbeeb/TAPS](https://github.com/Moe-Zbeeb/TAPS)
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+
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+ ## Model Details
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+ This checkpoint is a lightweight, single-layer Llama-style drafter (~0.8B parameters). It is intended to be used in a speculative decoding pipeline to propose future tokens, which are then verified in parallel by a larger target model.
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+
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+ ## Citation
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+ If you find this work useful, please cite:
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+ ```bibtex
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+ @article{zbib2026taps,
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+ title={TAPS: Task Aware Proposal Distributions for Speculative Sampling},
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+ author={Zbib, Mohamad and Bazzi, Mohamad and Mohanna, Ammar and Ghanem, Bernard and Hammoud, Hasan Abed Al Kader},
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+ year={2026},
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+ note={Technical report}
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+ }
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+ ```