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axolotl/examples/olmo3/README.md
NanoCode012 006f226270 Feat: add Olmo3 (BC with Olmo and Olmo2) (#3275)
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* chore: update docs following feedback

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* chore: add olmo to readme
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# Finetune Allenai's Olmo 3 with Axolotl
[Olmo 3](https://huggingface.co/collections/allenai/olmo-3) are a family of 7B and 32B models open source models trained by The Allen Institute for Artificial Intelligence.
This guide shows how to fine-tune it with Axolotl with multi-turn conversations and proper masking.
## Getting started
1. Install Axolotl following the [installation guide](https://docs.axolotl.ai/docs/installation.html).
Here is an example of how to install from pip:
```bash
# Ensure you have a compatible version of Pytorch installed
pip3 install packaging setuptools wheel ninja
pip3 install --no-build-isolation 'axolotl[flash-attn]>=0.12.0'
# Install Cut Cross Entropy
python scripts/cutcrossentropy_install.py | sh
```
2. Run the finetuning example:
```bash
axolotl train examples/olmo3/olmo3-7b-qlora.yaml
```
Let us know how it goes. Happy finetuning! 🚀
### TIPS
- The example config can be re-used for Olmo and Olmo 2.
- You can run a full finetuning by removing the `adapter: qlora` and `load_in_4bit: true` from the config.
- Read more on how to load your own dataset at [docs](https://docs.axolotl.ai/docs/dataset_loading.html).
- The dataset format follows the OpenAI Messages format as seen [here](https://docs.axolotl.ai/docs/dataset-formats/conversation.html#chat_template).
## Optimization Guides
Please check the [Optimizations doc](https://docs.axolotl.ai/docs/optimizations.html).
## Related Resources
- [Olmo 3 Blog](https://allenai.org/blog/olmo3)
- [Axolotl Docs](https://docs.axolotl.ai)
- [Axolotl Website](https://axolotl.ai)
- [Axolotl GitHub](https://github.com/axolotl-ai-cloud/axolotl)
- [Axolotl Discord](https://discord.gg/7m9sfhzaf3)