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t-5-comedy

Text2Text Generation
Transformers
PyTorch
English
t5
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text-generation-inference
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metadata
license: mit
datasets:
  - zachgitt/comedy-transcripts
language:
  - en
pipeline_tag: text2text-generation
library_name: transformers

Stand-Up Comic Assistant Model

Model Description

This model is designed as an assistant for stand-up comedians, providing suggestions, ideas, and content generation to support the creative process. It's trained on a diverse set of comedy transcripts, aiming to capture the essence of humor from various styles and contexts.

How It Works

The model is based on google/flan-t5-small, a powerful and efficient transformer model optimized for language understanding and generation tasks. It has been fine-tuned on the zachgitt/comedy-transcripts dataset, which includes a wide range of stand-up comedy routines.

Intended Use

  • Idea Generation: Generate prompts or comedy concepts based on current trends, historical events, or user input.
  • Content Creation: Assist in writing jokes, sketches, or full stand-up routines.
  • Interactive Comedy: Engage with users by providing humorous responses in a conversational setting.

Training

The model was trained using the transformers library on a dataset of stand-up comedy transcripts. The training process focused on understanding context, delivering punchlines, and preserving the comedic timing that's essential in stand-up comedy.

Training Data

The dataset zachgitt/comedy-transcripts was used, which includes transcripts from various comedians across different eras of stand-up comedy.

Limitations and Biases

  • Contextual Limitations: While the model understands a range of comedic styles, it may not always align with the nuances of personal taste in humor.
  • Cultural Sensitivity: The dataset includes historical content that may not be suitable or sensitive to current cultural contexts.
  • Language Biases: The model may reflect biases present in the training data, which consists of primarily English-language comedy routines.

Future Work

This model is a work in progress. Planned improvements include:

  • Expanding the dataset with more diverse and contemporary sources.
  • Implementing feedback loops to refine the model's sense of humor based on user interactions.
  • Enhancing the model's understanding of different comedic devices like satire, irony, and slapstick.

Acknowledgements

Thanks to all the contributors of the zachgitt/comedy-transcripts dataset and the teams behind google/flan-t5-small for providing the foundational models and tools that made this project possible.

Disclaimer: This model is intended for creative and entertainment purposes. It should be used responsibly, considering the potential for generating content that may be offensive or inappropriate in certain contexts.