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2 changes: 0 additions & 2 deletions docs/source/_toctree.yml
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title: Community Tutorials
- local: lora_without_regret
title: LoRA Without Regret
- local: sentiment_tuning
title: Sentiment Tuning
- local: multi_adapter_rl
title: Multi Adapter RLHF
title: Examples
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2 changes: 0 additions & 2 deletions docs/source/example_overview.md
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Expand Up @@ -36,8 +36,6 @@ These notebooks are easier to run and are designed for quick experimentation wit
Legacy / Older Notebooks

- [`best_of_n.ipynb`](https://github.com/huggingface/trl/tree/main/examples/notebooks/best_of_n.ipynb): This notebook demonstrates how to use the "Best of N" sampling strategy using TRL when fine-tuning your model with PPO.
- [`gpt2-sentiment.ipynb`](https://github.com/huggingface/trl/tree/main/examples/notebooks/gpt2-sentiment.ipynb): This notebook demonstrates how to reproduce the GPT2 imdb sentiment tuning example on a jupyter notebook.
- [`gpt2-sentiment-control.ipynb`](https://github.com/huggingface/trl/tree/main/examples/notebooks/gpt2-sentiment-control.ipynb): This notebook demonstrates how to reproduce the GPT2 sentiment control example on a jupyter notebook.

## Scripts

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31 changes: 0 additions & 31 deletions docs/source/sentiment_tuning.md

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2 changes: 0 additions & 2 deletions examples/notebooks/README.md
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Expand Up @@ -13,5 +13,3 @@ This directory contains a collection of Jupyter notebooks that demonstrate how t
Legacy / Older Notebooks

- [`best_of_n.ipynb`](https://github.com/huggingface/trl/tree/main/examples/notebooks/best_of_n.ipynb): This notebook demonstrates how to use the "Best of N" sampling strategy using TRL when fine-tuning your model with PPO.
- [`gpt2-sentiment.ipynb`](https://github.com/huggingface/trl/tree/main/examples/notebooks/gpt2-sentiment.ipynb): This notebook demonstrates how to reproduce the GPT2 imdb sentiment tuning example on a jupyter notebook.
- [`gpt2-sentiment-control.ipynb`](https://github.com/huggingface/trl/tree/main/examples/notebooks/gpt2-sentiment-control.ipynb): This notebook demonstrates how to reproduce the GPT2 sentiment control example on a jupyter notebook.
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