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Haikusian / README.md
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metadata
license: openrail
language:
  - en
datasets:
  - HuggingFaceFW/fineweb

Model Card for neoncortex/Haikusian

Model Details

Model Description

This model and associated dataset are a WIP.

Comments and contributions are welcome.

Haikusian is a language model specialized in generating haiku poetry, trained using a custom syllable-based tokenizer and a unique dataset of haikus. The model leverages recent advances in natural language generation to produce creative and structurally valid haiku poems while adhering to the traditional 5-7-5 syllable pattern across three lines.

Developed by RoboApocalypse (Neon Cortex), Haikusian represents an exploration into the artistic capabilities of AI systems. By combining computational linguistics techniques with neural networks, this model aims to generate poetic and culturally enriching content, pushing the boundaries of what AI can achieve in the creative domain.

Key features of Haikusian include:

  • Custom syllable tokenizer: A novel tokenization approach that splits text into syllables, allowing the model to learn and generate haikus at the syllable level.
  • Haiku-specific training data: A meticulously curated dataset of haiku poems from various sources, ensuring the model captures the nuances and structure of this poetic form.
  • Reinforced with synthetic data: Further fine-tuned on a synthetically generated dataset of haikus, enhancing the model's ability to produce coherent and thematically consistent outputs.
  • Syllable pattern enforcement: Built-in mechanisms to ensure generated haikus adhere to the 5-7-5 syllable pattern across three lines, a defining characteristic of traditional haiku poetry.
  • Open-source and transparent: Released under the OpenRAIL license, promoting open science, responsible development, and potential commercial applications of this creative AI technology.

Whether for artistic exploration, educational purposes, or simply appreciating the intersection of technology and culture, Haikusian offers a unique perspective on the capabilities of language models in the realm of poetry generation.

  • Developed by: Neon Cortex
  • Funded by: Neon Cortex
  • Shared by: RoboApocalypse
  • Model type: TBA
  • Language(s): English (en)
  • License: OpenRAIL

Model Sources

Uses

Direct Use

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Downstream Use [optional]

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Out-of-Scope Use

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Bias, Risks, and Limitations

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Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

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Training Details

Training Data

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Training Procedure

Preprocessing [optional]

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Training Hyperparameters

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Speeds, Sizes, Times [optional]

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Evaluation

Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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Summary

Model Examination [optional]

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

  • Hardware Type: [More Information Needed]
  • Hours used: [More Information Needed]
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Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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Citation [optional]

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APA:

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Glossary [optional]

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Model Card Authors [optional]

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Model Card Contact

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