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README.md
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- 490M parameters (360M non-embedding parameters)
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- 24 transformer layers
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- 14 attention heads for queries and 2 for key/values (GQA architecture)
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- Support for 32,768 context length
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- Advanced features like RoPE positional embeddings, SwiGLU activations, and RMSNorm
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- 490M parameters (360M non-embedding parameters)
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- 24 transformer layers
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- 14 attention heads for queries and 2 for key/values (GQA architecture)
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---
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### 🌐 Website
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You can find more of my models, projects, and information on my official website:
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- **[artificialguy.com](https://artificialguy.com/)**
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### 💖 Support My Work
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If you find this model useful, please consider supporting my work. It helps me cover server costs and dedicate more time to new open-source projects.
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- **Patreon:** [Support on Patreon](https://www.patreon.com/user?u=81570187)
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- **Ko-fi:** [Buy me a Ko-fi](https://ko-fi.com/artificialguybr)
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- **Buy Me a Coffee:** [Buy me a Coffee](https://buymeacoffee.com/jvkape)
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- Support for 32,768 context length
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- Advanced features like RoPE positional embeddings, SwiGLU activations, and RMSNorm
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