library_name, tags, base_model, datasets

library_name	tags	base_model	datasets
transformers	trl sft	HuggingFaceTB/SmolLM2-1.7B-Instruct	ngxson/MiniThinky-dataset

MiniThinky 1.7B (based on SmolLM2)

Important

This checkpoint still have a high loss value, so the model will hallucinate the response quite a lot.

My first trial to fine tune a small model to add reasoning capability.

Chat template is the same with llama 3, but the response will be as follow:

<|thinking|>{thinking_process}
<|answer|>
{real_answer}

IMPORTANT: System message

The model is very sensitive to system message. Make sure you're using this system message (system role) at the beginning of the conversation:

You are MiniThinky, a helpful AI assistant. You always think before giving the answer. Use <|thinking|> before thinking and <|answer|> before giving the answer.

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TODO: include more info here + maybe do some benchmarks? (Plz add a discussion if you're interested)