* feat(doc): update gpt-oss readme * fix: caps * feat: add toolcalling section * feat: add example tool dataset to docs * chore: update
72 lines
2.6 KiB
Markdown
72 lines
2.6 KiB
Markdown
# Finetune OpenAI's GPT-OSS with Axolotl
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[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.
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This guide shows how to fine-tune it with Axolotl with multi-turn conversations and proper masking.
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## Getting started
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1. Install Axolotl following the [installation guide](https://docs.axolotl.ai/docs/installation.html). You need to install from main as GPT-OSS is only on nightly or use our latest [Docker images](https://docs.axolotl.ai/docs/docker.html).
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Here is an example of how to install from main for pip:
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```bash
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# Ensure you have Pytorch installed (Pytorch 2.6.0 min)
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git clone https://github.com/axolotl-ai-cloud/axolotl.git
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cd axolotl
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pip3 install packaging==23.2 setuptools==75.8.0 wheel ninja
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pip3 install --no-build-isolation -e '.[flash-attn]'
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```
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2. Choose one of the following configs below for training the 20B model.
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```bash
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# LoRA SFT linear layers & 2 experts (1x48GB @ ~47GiB)
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# (only linear layers @ ~44GiB)
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axolotl train examples/gpt-oss/gpt-oss-20b-sft-lora-singlegpu.yaml
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# FFT SFT with offloading (2x24GB @ ~21GiB/GPU)
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axolotl train examples/gpt-oss/gpt-oss-20b-fft-fsdp2-offload.yaml
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# FFT SFT (8x48GB @ ~36GiB/GPU or 4x80GB @ ~46GiB/GPU)
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axolotl train examples/gpt-oss/gpt-oss-20b-fft-fsdp2.yaml
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```
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Notes:
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- 120B coming soon!
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- Memory usage taken from `device_mem_reserved(gib)` from logs.
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### Tool use
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GPT-OSS has a comprehensive tool understanding. Axolotl supports tool calling datasets for Supervised Fine-tuning.
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Here is an example dataset config:
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```yaml
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datasets:
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- path: Nanobit/text-tools-2k-test
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type: chat_template
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```
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See [Nanobit/text-tools-2k-test](https://huggingface.co/datasets/Nanobit/text-tools-2k-test) for the sample dataset.
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Refer to [our docs](https://docs.axolotl.ai/docs/dataset-formats/conversation.html#using-tool-use) for more info.
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### TIPS
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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 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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## Optimization Guides
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- [Multi-GPU Training](https://docs.axolotl.ai/docs/multi-gpu.html)
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- [Multi-Node Training](https://docs.axolotl.ai/docs/multi-node.html)
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## Related Resources
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- [GPT-OSS Blog](https://openai.com/index/introducing-gpt-oss/)
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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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