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@@ -167,9 +167,11 @@ Because they wanted someone who could communicate complex ideas without making a
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  ```
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  ### Use case 3: RLHF
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- PairRM has been trained on various high-quality and large-scale dataset with human preference annotations and exhibits great correlation with human preferences with an extremly small model size (0.4B), approching the performance of GPT-4.
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- We believe PairRM will power the alignment of LLM in an efficient and effective way.
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- With a `blender.compare()` function, you can easily apply PairRM to poopular RLHF toolkits like [trl](https://huggingface.co/docs/trl/index).
 
 
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  **🔥 Check more details on our example jupyter notebook usage: [`blender_usage.ipynb`](https://github.com/yuchenlin/LLM-Blender/blob/main/blender_usage.ipynb)**
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@@ -184,7 +186,7 @@ Learn more in our LLM-Blender Github [README.md](https://github.com/yuchenlin/LL
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  ### Context length
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  | PairRanker type | Source max length | Candidate max length | Total max length |
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  |:-----------------:|:-----------------:|----------------------|------------------|
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- | [pair-ranker](https://huggingface.co/llm-blender/pair-ranker) | 128 | 128 | 384 |
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  | [PairRM](https://huggingface.co/llm-blender/pair-reward-model/) (This model) | 1224 | 412 | 2048 |
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  ```
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  ### Use case 3: RLHF
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+ PairRM has been trained on various high-quality and large-scale datasets with human preference annotations
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+ and shown great correlation with human preferences with an extremely small model size (0.4B),
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+ approching the performance of GPT-4.
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+ PairRM will better help the future alignment of LLMs in a more efficient and effective way.
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+ With a `blender.compare()` function, you can apply PairRM to popular RLHF toolkits such as [trl](https://huggingface.co/docs/trl/index).
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  **🔥 Check more details on our example jupyter notebook usage: [`blender_usage.ipynb`](https://github.com/yuchenlin/LLM-Blender/blob/main/blender_usage.ipynb)**
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  ### Context length
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  | PairRanker type | Source max length | Candidate max length | Total max length |
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  |:-----------------:|:-----------------:|----------------------|------------------|
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+ | [pair-ranker](https://huggingface.co/llm-blender/pair-ranker) (our previous version) | 128 | 128 | 384 |
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  | [PairRM](https://huggingface.co/llm-blender/pair-reward-model/) (This model) | 1224 | 412 | 2048 |
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