MiniThinky 1.7B (based on SmolLM2)

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.


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

Downloads last month
24
Safetensors
Model size
1.71B params
Tensor type
F32
·
Inference Providers NEW
This model is not currently available via any of the supported third-party Inference Providers, and the model is not deployed on the HF Inference API.

Model tree for ngxson/MiniThinky-1.7B-SmolLM2

Finetuned
(33)
this model
Quantizations
2 models

Dataset used to train ngxson/MiniThinky-1.7B-SmolLM2

Collection including ngxson/MiniThinky-1.7B-SmolLM2