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

---
license: cc-by-4.0
task_categories:
- text-generation
language:
- en
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: conversation
list:
- name: content
dtype: string
- name: role
dtype: string
- name: generated_message
struct:
- name: content
dtype: string
- name: reasoning_content
dtype: 'null'
- name: role
dtype: string
- name: tool_calls
sequence: 'null'
- name: finish_reason
dtype: string
splits:
- name: train
num_bytes: 2345354821
num_examples: 659808
download_size: 1223042658
dataset_size: 2345354821
---

# 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}
}
```