| # SPM-350M |
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| **SPM-350M** is a 350 million parameter decoder-only language model developed by **Syclient**. |
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| The model is designed for research, education, conversational AI, and efficient language model development. SPM-350M serves as the foundation of the Strategic Pretrained Model (SPM) family and represents Syclient's first large-scale language model project. |
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| ## Overview |
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| SPM-350M is part of the SPM (Strategic Pretrained Model) family, a research initiative focused on building efficient and scalable language models from the ground up. |
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| The project explores language modeling, instruction following, conversational AI, tokenizer design, and future experimental architectures. |
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| ## Model Specifications |
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| | Property | Value | |
| | --------------------------- | ------------------------ | |
| | Model Name | SPM-350M | |
| | Organization | Syclient | |
| | Architecture | Decoder-only Transformer | |
| | Parameters | 348.7M | |
| | Hidden Size | 1024 | |
| | Layers | 24 | |
| | Attention Heads | 16 | |
| | KV Heads | 8 | |
| | Context Length | 2048 | |
| | Recommended Sequence Length | 1024 | |
| | Vocabulary Size | 32,000 | |
| | Primary Language | English | |
| | Secondary Language | Turkish | |
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| ## Training Data |
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| SPM-350M was trained using a mixture of publicly available datasets, including: |
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| * FineWeb-Edu |
| * Wikipedia |
| * UltraChat |
| * OpenAssistant |
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| The training corpus was curated for research, conversational modeling, and general language understanding tasks. |
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| ## Model Weights |
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| The model weights are available on Hugging Face. |
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| Coming Soon. |
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| ## Intended Use |
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| SPM-350M is intended for: |
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| * Research |
| * Education |
| * Conversational AI |
| * Text Generation |
| * Experimentation |
| * Language Model Development |
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| ## Limitations |
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| SPM-350M is an experimental research model. |
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| The model may: |
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| * Generate incorrect information |
| * Produce biased outputs |
| * Make reasoning mistakes |
| * Hallucinate facts |
| * Fail on complex tasks |
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| Users should independently verify important information. |
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| ## Roadmap |
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| * [x] SPM-70M Vertigo |
| * [x] SPM-350M Foundation |
| * [x] SPM-350M Chat Edition |
| * [ ] SPM-350M Ultra Edition |
| * [ ] SPM-1.2B |
| * [ ] SPM Flux Architecture |
| * [ ] SPM-8B |
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| ## Vision |
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| Our goal is to build efficient language models that are accessible, practical, and scalable. |
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| Rather than focusing solely on model size, the SPM project explores how far efficiency, data quality, and architecture design can be pushed within limited computational resources. |
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| ## License |
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| Apache License 2.0 |
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| ## Citation |
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| ```bibtex |
| @misc{spm350m2026, |
| title={SPM-350M}, |
| author={Syclient}, |
| year={2026}, |
| publisher={GitHub} |
| } |
| ``` |
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| **Building efficient language models from the ground up.** |
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