yunjae-won/mpq3_llama8b_sft_dpo_beta1e-1_step3584
The yunjae-won/mpq3_llama8b_sft_dpo_beta1e-1_step3584 is an 8 billion parameter language model. This model is a fine-tuned variant, likely based on the Llama architecture, optimized through Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO). Its specific differentiators and primary use cases are not detailed in the provided model card, which indicates "More Information Needed" for most sections.
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Model Overview
This model, yunjae-won/mpq3_llama8b_sft_dpo_beta1e-1_step3584, is an 8 billion parameter language model. It has been pushed to the Hugging Face Hub as a transformers model. The model name suggests it has undergone Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO) with a beta value of 1e-1, indicating a specific training methodology aimed at aligning model outputs with human preferences.
Key Characteristics
- Parameter Count: 8 billion parameters.
- Training Method: Implies a combination of Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO).
- Context Length: The model supports a context length of 8192 tokens.
Current Limitations
As per the provided model card, detailed information regarding the model's developer, specific architecture, language(s) supported, license, direct and downstream uses, out-of-scope uses, biases, risks, limitations, training data, training procedure, and evaluation results is currently marked as "More Information Needed." Users should be aware that comprehensive details on its performance, intended applications, and potential issues are not yet available.