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README.md
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- mini-llm
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- text-generation-inference
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- lm-evaluation-harness
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datasets:
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- openai/gsm8k
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- openai/openai_humaneval
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<img src="OfficialAtomight.png" alt="Atomight Logo" width="500" style="max-width: 100%;">
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</p>
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**Atomight-V2.1-0.5B-Inference** is an ultra-compact, reasoning-oriented causal language model developed under the **[Atomight Ecosystem](https://huggingface.co/NovatasticRoScript/collections)**. Built on a Qwen-derived 494M parameter foundation, the model has been refined using **GRPO (Group Relative Policy Optimization)** reinforcement tuning.
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Despite its tiny physical footprint, Atomight-V2.1-0.5B targets highly efficient edge-device reasoning, structured text outputs, lightweight coding assistance, and rapid deployment workflows under severe compute constraints.
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- mini-llm
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- text-generation-inference
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- lm-evaluation-harness
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- atomight
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datasets:
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- openai/gsm8k
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- openai/openai_humaneval
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<img src="OfficialAtomight.png" alt="Atomight Logo" width="500" style="max-width: 100%;">
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</p>
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**Atomight-V2.1-0.5B-Inference** is an ultra-compact, reasoning-oriented causal language model developed under the **[Atomight Ecosystem](https://huggingface.co/NovatasticRoScript/collections)**. Currently our **best model** up-to-date. Built on a Qwen-derived 494M parameter foundation, the model has been refined using **GRPO (Group Relative Policy Optimization)** reinforcement tuning.
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Despite its tiny physical footprint, Atomight-V2.1-0.5B targets highly efficient edge-device reasoning, structured text outputs, lightweight coding assistance, and rapid deployment workflows under severe compute constraints.
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