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@@ -100,7 +100,6 @@ We found that using a strong reward model for annotating preference optimization
| Llama 3 Instruct 8B KTO v0.2 | [princeton-nlp/Llama-3-Instruct-8B-KTO-v0.2](https://huggingface.co/princeton-nlp/Llama-3-Instruct-8B-KTO-v0.2) | 34.1 | 36.4 | 30.9 |
| Llama 3 Instruct 8B ORPO v0.2 | [princeton-nlp/Llama-3-Instruct-8B-ORPO-v0.2](https://huggingface.co/princeton-nlp/Llama-3-Instruct-8B-ORPO-v0.2) | 34.1 | 32.1 | 27.3 |
| Llama 3 Instruct 8B R-DPO v0.2 | [princeton-nlp/Llama-3-Instruct-8B-RDPO-v0.2](https://huggingface.co/princeton-nlp/Llama-3-Instruct-8B-RDPO-v0.2) | 38.1 | 33.8 | 28.2 |
| Llama 3 Instruct 8B SimPO v0.2 | [princeton-nlp/Llama-3-Instruct-8B-SimPO-v0.2](https://huggingface.co/princeton-nlp/Llama-3-Instruct-8B-SimPO-v0.2) | 48.0 | 45.8 | 35.1 |
| Llama 3 Instruct 8B SimPO v0.2 | [princeton-nlp/Llama-3-Instruct-8B-SimPO-v0.2](https://huggingface.co/princeton-nlp/Llama-3-Instruct-8B-SimPO-v0.2) | 53.7 | 47.5 | 36.5 |
### Use our models for inference