More details about the examples of on-policy distillation
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Description
Thanks your fantastic job!
Could you provide more details about the examples of on-policy distillation? It is mentioned in examples/on_policy_distillation/Readme.md that the Qwen3-8B-Base model fine-tuned with supervised fine-tuning (SFT) on part of the [OpenThoughts3-1.2M] dataset is used. Would it be possible to make this SFT model publicly available, or inform us of the SFT details such as the number of epochs and the learning rate?
@ahxt
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Review examples/on_policy_distillation/Readme.md and the referenced Qwen3-8B-Base SFT description. Confirm the SFT model's availability and the training details requested, then update the example documentation with information supplied by the maintainers. Done means the README clearly documents those details or explains that the model or details cannot be shared.
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Assessment
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100