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This is a library of the lora's I've trained on classic literature. Using both Llama-2 and Llama-3 formats.

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Classical Literature Loras Welcome to the Classical Literature Loras repository! This project is dedicated to creating Low-Rank Adaptation (LoRA) models based on classical literature, bringing the timeless wisdom and beauty of these works into the modern age of AI and machine learning.

Overview In this repository, you will find a curated list of links to my Hugging Face repository, where each link points to a LoRA model trained on various classical literary works. These models can be used for a range of natural language processing (NLP) tasks, such as text generation, summarization, translation, and more.

Hugging Face Repositories Below is the list of classical literature Loras available on my Hugging Face profile. Click on the links to access each model, view the training details, and explore usage examples.

  1. Alice and Wonderland by Lewis Carroll
    The Alice in Wonderland LoRA model captures the playful and imaginative spirit of Lewis Carroll's classic tale. It is perfect for generating text that mimics the whimsical and nonsensical style of the original story. Whether you're looking to create your own fantastical adventures or add a touch of Wonderland magic to your writing, this model will provide a delightful and quirky touch.

  2. Illad by Homer
    The Illa LORA model embodies the mystical and dreamlike essence of ancient mythology. With its ability to weave together threads of mythological lore and poetic license, this model brings forth tales of forgotten heroes, mythical creatures, and hidden realms waiting to be discovered. Let its words transport you to a world where gods and mortals coexist, where legends are born anew, and where the boundaries between reality and fantasy blur.

  3. Crime and Punishment By Fyodor Dostoyevsky
    The Crime and Punishment Lora model, captures the classic novel by Fyodor Dostoyevsky, seamlessly integrates the hardboiled detective atmosphere of LA Noire. Its responses exude the gritty charm of 1940s Los Angeles, complete with slang, jazz music, and the ever-present threat of corruption lurking beneath the glittering facade of Hollywood's Golden Age. Like the iconic detective protagonist, players must navigate through a web of moral ambiguity and unravel complex cases filled with intrigue and suspense. The gameplay becomes an immersive journey into the darkest corners of human nature, challenging players to confront their own values and beliefs along the way.

  4. Moby Dick by Herman Melville
    The Moby Dick Lora model, named after Herman Melville's literary masterpiece, infuses AI models with a thrilling adventurous flair. Inspired by Captain Ahab's relentless pursuit of the elusive whale, this model is fueled by a relentless pursuit of knowledge and understanding. It embarks on a journey to explore the depths of human experience, delving into the complexities of the human psyche, and unraveling the mysteries of existence. With each quest, the model returns with richer insights, wiser words, and more captivating stories to share. Whether navigating the treacherous seas of life or charting uncharted territories of the mind, the Moby Dick Lora model brings adventure, wisdom, and wisdom to any endeavor it undertakes.

  5. Tale of Two Cities By Charles Dickens
    The Tale of Two Cities Lora model, drawing inspiration from Charles Dickens' timeless classic, infuses AI models with a hauntingly mysterious flair. Its responses evoke the turbulent era of revolutionary France, where the lines between good and evil, love and hate, and life and death blur. This model masterfully weaves together historical facts, philosophical musings, and emotional depth to create a compelling narrative that leaves readers/users yearning for more. As the story unfolds, so does the enigma surrounding the characters, events, and underlying themes, inviting multiple interpretations and endless discussion.

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This is a library of the lora's I've trained on classic literature. Using both Llama-2 and Llama-3 formats.

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