Pclanglais/Epstein
Pclanglais/Epstein is a 13 billion parameter generative LLM, fine-tuned from Llama-13B, specifically designed for English literature generation. Trained on 4,000 excerpts of public domain English literature and synthetic annotations, it creates literary texts based on twenty potential features. This model excels at generating creative narratives, acting as the generative counterpart to the analytical Brahe model.
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Pclanglais/Epstein: A Generative LLM for English Literature
Epstein is a 13 billion parameter large language model, fine-tuned from Llama-13B, with a specialized focus on generating English literary texts. It was trained on a dataset comprising 4,000 excerpts of public domain English or English-translated literature, augmented with synthetic and manual annotations. The model's core functionality involves generating text based on up to twenty distinct literary features provided as input.
Key Capabilities
- Literary Text Generation: Creates diverse literary content based on specified parameters.
- Feature-Driven Generation: Utilizes a comprehensive set of annotations including:
- Content: Summary, Trope, Narrative arc, Enunciation, Tone, Genre, Intertextuality, Speech standard, Literary form.
- Context: Active/Mentioned characters, Quoted works, Absolute/Fuzzy place, Fuzzy/Absolute time, Time setting, Diegetic time.
- Companion to Brahe: Functions as the generative inverse of the analytical model Brahe, both named after characters from Daniele del Giudice's Atlante occidentale.
Good For
- Creative Writing Assistance: Ideal for authors or developers looking to generate literary drafts or explore narrative possibilities.
- Literary Experimentation: Useful for experimenting with different literary styles, genres, and narrative structures by manipulating input features.
- Educational Tools: Can be integrated into tools for studying literary elements and their impact on text generation.