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@@ -60,7 +60,7 @@ We have observed that, in some cases, adding an additional SFT loss can help imp
## Released Models
### v0.1
Below is the complete list of models evaluated in our preprint. We used the [HuggingFaceH4/ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized) dataset to train the Mistral Base and Llama3 Base models, the [princeton-nlp/mistral-instruct-ultrafeedback](https://huggingface.co/princeton-nlp/mistral-instruct-ultrafeedback) dataset to train the Mistral Instruct models, and the [princeton-nlp/llama3-ultrafeedback](https://huggingface.co/princeton-nlp/llama3-ultrafeedback) dataset to train the Llama3 Instruct models. The latter two datasets are annotated by the [llm-blender/PairRM](https://huggingface.co/llm-blender/PairRM) model.
Below is the complete list of models evaluated in our preprint. We used the [HuggingFaceH4/ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized) dataset to train the Mistral Base and Llama3 Base models, the [princeton-nlp/mistral-instruct-ultrafeedback](https://huggingface.co/datasets/princeton-nlp/mistral-instruct-ultrafeedback) dataset to train the Mistral Instruct models, and the [princeton-nlp/llama3-ultrafeedback](https://huggingface.co/datasets/princeton-nlp/llama3-ultrafeedback) dataset to train the Llama3 Instruct models. The latter two datasets are annotated by the [llm-blender/PairRM](https://huggingface.co/llm-blender/PairRM) model.
models | | AE2 LC | AE2 WR | AH |
|------------------------------|-----------------------------------------------------------------------------------------------------------|:------:|:------:|:----:|