Update README.md
Browse filesNano-Butterfly
Nano-Butterfly is a custom AI model developed by Alexander Malik Pramono. This model is designed to perform a variety of tasks, ranging from natural language understanding to generating responses for applications that require advanced AI-driven interaction.
Overview
Nano-Butterfly is a state-of-the-art, lightweight AI model optimized for efficiency, ease of use, and a broad range of applications. With a focus on both performance and usability, it serves as an excellent starting point for developers and researchers looking to integrate cutting-edge AI capabilities into their projects.
Features:
High-quality, natural language understanding.
Efficient, lightweight model with fast inference speeds.
Built to be easily deployable across various environments.
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language:
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pipeline_tag: text-generation
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language:
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pipeline_tag: text-generation
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MIT License
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Copyright (c) 2025 Alexander Malik Pramono
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Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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Contributing
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Contributions are welcome! Please fork the repository, make your changes, and submit a pull request. All contributions must follow the code style of the project.
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