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axolotl/examples/gpt-oss/README.md

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# Finetune OpenAI's GPT-OSS with Axolotl
[GPT-OSS](https://huggingface.co/collections/openai/gpt-oss-68911959590a1634ba11c7a4) are a family of open-weight MoE models trained by OpenAI, released in August 2025. There are two variants: 20B and 120B.
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 Pytorch installed (Pytorch 2.6.0 min)
pip3 install packaging==23.2 setuptools==75.8.0 wheel ninja
pip3 install --no-build-isolation 'axolotl[flash-attn]>=0.12.0'
```
2. Choose one of the following configs below for training the 20B model.
```bash
# LoRA SFT linear layers & 2 experts (1x48GB @ ~47GiB)
# (only linear layers @ ~44GiB)
axolotl train examples/gpt-oss/gpt-oss-20b-sft-lora-singlegpu.yaml
# FFT SFT with offloading (2x24GB @ ~21GiB/GPU)
axolotl train examples/gpt-oss/gpt-oss-20b-fft-fsdp2-offload.yaml
# FFT SFT (8x48GB @ ~36GiB/GPU or 4x80GB @ ~46GiB/GPU)
axolotl train examples/gpt-oss/gpt-oss-20b-fft-fsdp2.yaml
```
Notes:
- 120B coming soon!
- Memory usage taken from `device_mem_reserved(gib)` from logs.
### Tool use
GPT-OSS has a comprehensive tool understanding. Axolotl supports tool calling datasets for Supervised Fine-tuning.
Here is an example dataset config:
```yaml
datasets:
- path: Nanobit/text-tools-2k-test
type: chat_template
```
See [Nanobit/text-tools-2k-test](https://huggingface.co/datasets/Nanobit/text-tools-2k-test) for the sample dataset.
Refer to [our docs](https://docs.axolotl.ai/docs/dataset-formats/conversation.html#using-tool-use) for more info.
### TIPS
- 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
- [Multi-GPU Training](https://docs.axolotl.ai/docs/multi-gpu.html)
- [Multi-Node Training](https://docs.axolotl.ai/docs/multi-node.html)
## Related Resources
- [GPT-OSS Blog](https://openai.com/index/introducing-gpt-oss/)
- [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)