McGill-NLP/llm2vec-gen-tulu-w-hard-negative
收藏Hugging Face2026-03-02 更新2026-03-29 收录
下载链接：
https://hf-mirror.com/datasets/McGill-NLP/llm2vec-gen-tulu-w-hard-negative
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资源简介：
---
dataset_info:
features:
- name: id
dtype: string
- name: question
dtype: string
- name: answer
dtype: string
- name: negative_question
dtype: string
- name: negative_answer
dtype: string
splits:
- name: original
num_bytes: 2034528644
num_examples: 805467
- name: Qwen3_17B
num_bytes: 3660909440
num_examples: 805467
- name: Qwen3_4B
num_bytes: 3696200913
num_examples: 805467
- name: Qwen3_8B
num_bytes: 3696485153
num_examples: 805467
download_size: 7133393300
dataset_size: 13088124150
configs:
- config_name: default
data_files:
- split: original
path: data/original-*
- split: Qwen3_17B
path: data/Qwen3_17B-*
- split: Qwen3_4B
path: data/Qwen3_4B-*
- split: Qwen3_8B
path: data/Qwen3_8B-*
---
# LLM2Vec-Gen
The dataset consists of generations based on the Tulu-3 SFT data ([https://huggingface.co/datasets/allenai/tulu-3-sft-mixture](allenai/tulu-3-sft-mixture)). These generations are intended to be used for training LLM2Vec-Gen models, serving as the target output for queries.
The `negative_question` in this dataset are generated by Gemini. This dataset consists of various splits. Each split corresponds to responses generated by a specific LLM, e.g., Qwen3-4B. The "original" split refers to the original Tulu-3 responses.
Each instance in split `M` typically includes:
- `id`: The original id.
- `question`: The original query.
- `answer`: The text generated by the model `M`.
- `negative_question`: The negative query generated by Gemini.
- `negative_answer`: The text generated by the model `M`.
## Usage
You can load the dataset using the Hugging Face datasets library.
``` python
from datasets import load_dataset
dataset = load_dataset("McGill-NLP/llm2vec-gen-tulu-w-hard-negative", split="Qwen3_4B")
```
提供机构：
McGill-NLP
