74 lines
2.1 KiB
Markdown
74 lines
2.1 KiB
Markdown
# Ministral3 2512 Thinking Fine-tuning
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This guide covers fine-tuning [Ministral3 2512](https://huggingface.co/collections/mistralai/ministral-3) with thinking capabilities using Axolotl. The thinking model enables explicit Chain-of-Thought reasoning with separate thinking and response sections.
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## Prerequisites
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Before starting, ensure you have:
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- Installed Axolotl (see [main README](../README.md))
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## Getting Started
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Run the thinking model fine-tuning:
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```bash
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axolotl train examples/ministral3/think/ministral3-3b-think-qlora.yaml
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```
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This config uses about 4.76 GiB VRAM.
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### Tips
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- Dataset uses multi-content format with `type: thinking` support. See [Dataset Format](#dataset-format) below.
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- You cannot mix `content: str` and `content: list[dict]`, otherwise, dataset loading will fail. Keep it consistent.
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## Dataset Format
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The thinking model requires the multi-content dataset format with support for an extra `role: thinking` within system and assistant messages.
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Example format:
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```json
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{
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"messages": [
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{
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"role": "system",
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"content": [
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{ "type": "text", "text": "{SYSTEM_PROMPT}"}
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]
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},
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{
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"role": "user",
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"content": [
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{ "type": "text", "text": "Solve this step by step: What is 15% of 240?"}
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]
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},
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{
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"role": "assistant",
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"content": [
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{
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"type": "thinking",
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"thinking": "I need to calculate 15% of 240. First, I'll convert 15% to decimal: 0.15. Then multiply: 0.15 × 240 = 36."
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},
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{
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"type": "text",
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"text": "To find 15% of 240, I'll multiply 240 by 0.15:\n\n240 × 0.15 = 36\n\nTherefore, 15% of 240 is 36."
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}
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]
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}
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]
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}
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```
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### Advanced Options
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The `thinking` section supports an optional `closed` parameter:
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```json
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{
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"type": "thinking",
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"thinking": "Internal reasoning here...",
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"closed": true // Default: true, controls adding the closing [/THINK] tag
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}
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```
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