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- Thinker
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- LlamaForCausalLM
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# **REASONING SMOLLM2 135M ON CUSTOM SYNTHETIC DATA**
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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. Fine-tuning a language model like SmolLM involves several steps, from setting up the environment to training the model and saving the results. Below is a detailed step-by-step guide based on the provided notebook file
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- Thinker
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- LlamaForCausalLM
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# **REASONING SMOLLM2 135M ON CUSTOM SYNTHETIC DATA**
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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. Fine-tuning a language model like SmolLM involves several steps, from setting up the environment to training the model and saving the results. Below is a detailed step-by-step guide based on the provided notebook file
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