Llama-3.3-70B-Instruct-Infinity-Instruct-0625

# Llama-3.3-70B-Instruct-Infinity-Instruct-0625 ## Dataset Description This dataset is part of the LK-Speculators collection for speculative decoding research. It contains 660K prompt-response pairs designed for training draft models that are used alongside Llama-3.3-70B-Instruct as the target model. The dataset was created by generating responses to the prompts from [Infinity-Instruct-0625](https://huggingface.co/datasets/BAAI/Infinity-Instruct) with [meta-llama/Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) at temperature=1. For more details on the training methodology and results, see our paper: [LK Losses: Direct Acceptance Rate Optimization for Speculative Decoding](https://arxiv.org/abs/2602.23881). ## Dataset Structure - **Format**: parquet - **Rows**: 659,808 ## Usage ```python from datasets import load_dataset dataset = load_dataset("nebius/Llama-3.3-70B-Instruct-Infinity-Instruct-0625") ``` ## License The dataset is released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) This dataset was collected using outputs from outputs from [meta-llama/Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct). Use of this model is additionally subject to the [Llama 3.3 Community License Agreement](https://github.com/meta-llama/llama-models/blob/main/models/llama3_3/LICENSE). Llama 3.3 is licensed under the Llama 3.3 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved. ## Citation ``` @misc{samarin2026lklosses, title = {LK Losses: Direct Acceptance Rate Optimization for Speculative Decoding}, author = {Alexander Samarin and Sergei Krutikov and Anton Shevtsov and Sergei Skvortsov and Filipp Fisin and Alexander Golubev}, year = {2026}, eprint = {2602.23881}, archivePrefix = {arXiv}, primaryClass = {cs.LG}, url = {https://arxiv.org/abs/2602.23881} } ```