Supervised fine-tuning refers to a machine learning technique where a pre-trained model is further trained on a specific task or dataset with labeled examples (supervised learning). The process involves taking a model that has been pre-trained on a large general dataset and then adapting it to a more focused task by continuing the training using task-specific data.
This model is test version, alignment-tuned model.
We utilize state-of-the-art instruction fine-tuning methods including direct preference optimization (DPO).
Runs of 4season final_model_test_v2 on huggingface.co
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