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license: apache-2.0 |
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datasets: |
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- voidful/mixed_inst_multi_chat |
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base_model: |
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- HuggingFaceTB/SmolLM2-360M |
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pipeline_tag: text-generation |
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Model Summary |
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SmolLM2 is a family of compact language models available in three size: 135M, 360M, and 1.7B parameters. They are capable of solving a wide range of tasks while being lightweight enough to run on-device. |
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SmolLM2 demonstrates significant advances over its predecessor SmolLM1, particularly in instruction following, knowledge, reasoning. The 360M model was trained on 4 trillion tokens using a diverse dataset combination: FineWeb-Edu, DCLM, The Stack, along with new filtered datasets we curated and will release soon. We developed the instruct version through supervised fine-tuning (SFT) using a combination of public datasets and our own curated datasets. We then applied Direct Preference Optimization (DPO) using UltraFeedback. |
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The instruct model additionally supports tasks such as text rewriting, summarization and function calling thanks to datasets developed by Argilla such as Synth-APIGen-v0.1. |
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For more details refer to: https://github.com/huggingface/smollm. You will find pre-training, post-training, evaluation and local inference code. |
