50f2b94d50
* add 120b and deepspeed zero3 examples * add a bit of flavor and cleanup gpt oss readme * fix: remove expert vram usage * fix: remove redundant EOS token from eot_tokens * feat: add 120B to docs --------- Co-authored-by: NanoCode012 <nano@axolotl.ai>
75 lines
2.5 KiB
Markdown
75 lines
2.5 KiB
Markdown
# 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. (for 120B, see [below](#training-120b))
|
|
|
|
```bash
|
|
# LoRA SFT linear layers (1x48GB @ ~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
|
|
```
|
|
|
|
Note: Memory usage taken from `device_mem_reserved(gib)` from logs.
|
|
|
|
### Training 120B
|
|
|
|
On 8xH100s
|
|
|
|
```bash
|
|
# FFT SFT with offloading (8x80GB @ ~49GiB/GPU)
|
|
axolotl train examples/gpt-oss/gpt-oss-120b-fft-fsdp2-offload.yaml
|
|
```
|
|
|
|
### 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)
|