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- Cultural Sensitivity: The dataset includes historical content that may not be suitable or sensitive to current cultural contexts.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.