006f226270
* feat: update cce to include olmo family * chore: update docs following feedback * feat: add olmo3 config * fix: clarify 3 methods * chore: add olmo to readme
49 lines
1.8 KiB
Markdown
49 lines
1.8 KiB
Markdown
# Finetune ByteDance's Seed-OSS with Axolotl
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[Seed-OSS](https://huggingface.co/collections/ByteDance-Seed/seed-oss-68a609f4201e788db05b5dcd) are a series of 36B parameter open source models trained by ByteDance's Seed Team.
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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).
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Here is an example of how to install from pip:
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```bash
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# Ensure you have a compatible version of Pytorch installed
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pip3 install packaging setuptools wheel ninja
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pip3 install --no-build-isolation 'axolotl[flash-attn]>=0.12.0'
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# Install Cut Cross Entropy
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python scripts/cutcrossentropy_install.py | sh
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```
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2. Run the finetuning example:
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```bash
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axolotl train examples/seed-oss/seed-oss-36b-qlora.yaml
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```
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This config uses about 27.7 GiB VRAM.
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Let us know how it goes. Happy finetuning! 🚀
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### TIPS
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- For inference, the official Seed Team recommends `top_p=0.95` and `temperature=1.1`.
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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 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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Please check the [Optimizations doc](https://docs.axolotl.ai/docs/optimizations.html).
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## Related Resources
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- [ByteDance Seed Website](https://seed.bytedance.com/)
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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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