persona-chat / README.md
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metadata
dataset_info:
  features:
    - name: personality
      sequence: string
    - name: utterances
      list:
        - name: candidates
          sequence: string
        - name: history
          sequence: string
  splits:
    - name: train
      num_bytes: 175333427
      num_examples: 16046
    - name: validation
      num_bytes: 30803403
      num_examples: 2832
  download_size: 101859610
  dataset_size: 206136830
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
size_categories:
  - 10K<n<100K
license: apache-2.0
task_categories:
  - text-generation

Persona-Chat

Dataset Summary

Persona-Chat is a high-quality multi-turn dialogue dataset designed to train conversational AI systems with consistent personality and style. Each participant in the dataset is assigned a persona—a short description or set of traits—which guides their responses throughout the conversation. This dataset enables AI models to learn to maintain coherent personas across dialogue turns and produce responses that reflect consistent characteristics, improving naturalness and engagement in human-like conversation.

The dataset contains real human conversations and captures both persona-driven and context-aware interactions. It is commonly used for research in dialogue modeling, persona-based chatbots, and human-AI interaction studies.


Data Structure

Fields

Field Description
personality List of persona traits describing a participant
utterances Multi-turn conversation data
├── candidates Candidate responses for the given turn
└── history Past dialogue turns preceding the current turn

Splits

Split Examples Size (bytes) Description
Train 16046 175333427 Used for model training
Validation 2832 30803403 Used for validation and tuning

Total dataset size: 206136830 bytes
Total number of dialogues: 18878


Usage Example

from datasets import load_dataset

ds = load_dataset("anezatra/persona-chat", split="train")
print(ds[0])

References

Zhang, S., Dinan, E., Urbanek, J., Szlam, A., Kiela, D., & Weston, J. (2018). Personalizing dialogue agents: I have a dog, do you have pets too?. arXiv preprint arXiv:1801.07243. (https://arxiv.org/abs/1801.07243)