README.md

---
library_name: transformers
tags:
- trl
- sft
base_model:
- HuggingFaceTB/SmolLM2-1.7B-Instruct
datasets:
- 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.`

---

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