80 lines
2.7 KiB
Markdown
80 lines
2.7 KiB
Markdown
# Finetune Ministral3 with Axolotl
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Ministral3 is a family of open-weight models from MistralAI found on [HuggingFace](https://huggingface.co/collections/mistralai/ministral-3). This guide shows how to fine-tune it with Axolotl with multi-turn conversations and proper masking.
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Please see [Thinking](#thinking) and [Vision](#vision) for their respective fine-tuning.
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Thanks to the team at MistralAI for giving us early access to prepare for these releases.
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Note: This is still experimental given it is based on transformers v5 RC.
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## Getting started
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1. Install Axolotl from source following the [installation guide](https://docs.axolotl.ai/docs/installation.html#sec-edge-build).
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2. Install [Cut Cross Entropy](https://docs.axolotl.ai/docs/custom_integrations.html#cut-cross-entropy) to reduce training VRAM usage.
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3. Swap to the Axolotl transformers v5 branch
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```bash
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cp examples/ministral3/ministral3-3b-qlora.yaml ministral3-3b-qlora.yaml
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git fetch
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git checkout transformers-v5
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# Install packages for transformers v5
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pip install -e .
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```
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4. Run the fine-tuning:
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```bash
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axolotl train ministral3-3b-qlora.yaml
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```
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Let us know how it goes. Happy finetuning! 🚀
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### Tips
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- We recommend adding the same/similar SystemPrompt that the model is tuned for. You can find this within the repo's files titled `SYSTEM_PROMPT.txt`.
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- You can run a full finetuning by removing the `adapter: qlora` and `load_in_4bit: true` from the config.
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- Read more on how to load your own dataset at [docs](https://docs.axolotl.ai/docs/dataset_loading.html).
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- The text dataset format follows the OpenAI Messages format as seen [here](https://docs.axolotl.ai/docs/dataset-formats/conversation.html#chat_template).
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### Thinking
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Ministral3 2512 model supports thinking capabilities, enabling Chain-of-Thought reasoning with explicit thinking steps.
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📚 **[See the Thinking fine-tuning guide →](./think/README.md)**
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### Vision
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Ministral3 2512 model also supports vision capabilities.
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📚 **[See the Vision fine-tuning guide →](./vision/README.md)**
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## Optimization Guides
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Please check the [Optimizations doc](https://docs.axolotl.ai/docs/optimizations.html).
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## Limitations
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We only support the `mistral-common` tokenizer for Supervised Fine-tuning at the moment and for `type: chat_template` only.
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In addition, we do not support overriding tokens yet.
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## Related Resources
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- [MistralAI Mistral3 Blog](https://mistral.ai/news/mistral-3)
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- [Axolotl Docs](https://docs.axolotl.ai)
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- [Axolotl Website](https://axolotl.ai)
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- [Axolotl GitHub](https://github.com/axolotl-ai-cloud/axolotl)
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- [Axolotl Discord](https://discord.gg/7m9sfhzaf3)
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## Future Work
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- Add parity to Preference Tuning, RL, etc.
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- Add parity to other tokenizer configs like overriding tokens.
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