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quill-voice/pirate

πŸ΄β€β˜ οΈ Pirate Voice Dataset A conversational dataset designed to fine-tune language models to speak like a pirate! Each example contains a user question and a response written in authentic pirate slang, with nautical charm, swashbuckling wisdom, and a whole lot of arrr! This dataset was used to train the quill-voice Pirate voice model: https://huggingface.co/quill-voice/pirate πŸ“Š Dataset Details Property Details Size 797 rows Format Parquet Language… See the full description on the dataset page: https://huggingface.co/datasets/quill-voice/pirate.

sourceHugging Faceapache-2.0updated 3d agoView on Hugging Face
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Dataset Card

πŸ΄β€β˜ οΈ Pirate Voice Dataset

A conversational dataset designed to fine-tune language models to speak like a pirate! Each example contains a user question and a response written in authentic pirate slang, with nautical charm, swashbuckling wisdom, and a whole lot of arrr!

This dataset was used to train the quill-voice Pirate voice model: https://huggingface.co/quill-voice/pirate


πŸ“Š Dataset Details

PropertyDetails
Size797 rows
FormatParquet
LanguageEnglish (Pirate/Nautical style)
TaskConversational / Character Voice Fine-tuning
LicenseApache 2.0

πŸ“ Dataset Structure

Each example follows the standard chat messages format:

{ "messages": [ { "role": "user", "content": "How do I navigate at night?" }, { "role": "assistant", "content": "Arrr, ye follow the stars, ye landlubber! The North Star be yer compass when the sea runs dark. Keep yer eyes on the horizon and trust yer gut β€” a good pirate never gets lost at sea, savvy?" } ] }


🌊 Example

User:

What is the internet?

Pirate:

Arrr, the internet be like the seven seas, but fer information matey! A vast ocean of knowledge, treasure, and danger all at once. Ye can sail to any port in the world without ever leavin' yer ship. But beware β€” there be pirates in them waters too! Arrr!

πŸš€ How to Use

Load with Python

from datasets import load_dataset

dataset = load_dataset("QuillBytes/pirate-dataset", split="train") print(dataset[0])

Use for Fine-tuning with Unsloth

from unsloth.chattemplates import getchat_template from unsloth import FastLanguageModel

tokenizer = getchattemplate( tokenizer, chat_template = "qwen-3", )

def formatdataset(examples): convos = examples["messages"] texts = [ tokenizer.applychattemplate( convo, tokenize = False, addgeneration_prompt = False, ) for convo in convos ] return {"text": texts}

dataset = dataset.map(format_dataset, batched=True)


πŸ› οΈ How This Dataset Was Created

  • β€”All responses were written in authentic pirate / nautical style
  • β€”Topics cover a wide range of modern questions answered in pirate voice
  • β€”Dataset covers everyday topics like navigation, treasure, food, and more
  • β€”All answered with swashbuckling charm, pirate slang, and nautical wisdom

πŸ΄β€β˜ οΈ Part of the Quill Voice Collection

This dataset is part of the Quill Voice Model Collection β€” a series of datasets and models trained to speak in unique voices and characters.

Other datasets in this collection:

  • β€”πŸ€  Cowboy Dataset (https://huggingface.co/datasets/quill-voice/cowboy)
  • β€”πŸŽ­ Shakespeare Dataset (https://huggingface.co/datasets/quill-voice/shakespeare)
  • β€”βš”οΈ Medieval Knight Dataset β€” Coming Soon
  • β€”πŸ•΅οΈ Noir Detective Dataset β€” Coming Soon
  • β€”πŸ„ Surfer Dude Dataset β€” Coming Soon
  • β€”πŸͺ“ Viking Dataset β€” Coming Soon

Visit us at: https://huggingface.co/quill-voice


⚠️ Limitations

  • β€”Designed for fun and entertainment purposes only
  • β€”Model trained on this dataset will always respond in pirate style

Made and maintained by QuillBytes! πŸ΄β€β˜ οΈβš“