yunjae-won/mpq3_llama8b_sft_dpo_beta1e-1_step2560
The yunjae-won/mpq3_llama8b_sft_dpo_beta1e-1_step2560 is an 8 billion parameter language model developed by yunjae-won. This model is a fine-tuned variant, likely based on the Llama architecture, and has undergone 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.
Loading preview...
Model Overview
This model, yunjae-won/mpq3_llama8b_sft_dpo_beta1e-1_step2560, is an 8 billion parameter language model. It has been developed by yunjae-won and appears to be a fine-tuned version, incorporating both Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO) techniques.
Key Characteristics
- Parameter Count: 8 billion parameters.
- Context Length: Supports an 8192-token context window.
- Training Method: Utilizes Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO).
Current Status
The provided model card indicates that significant details regarding its specific architecture, language support, license, training data, evaluation results, and intended use cases are currently marked as "More Information Needed." Users should consult future updates for comprehensive details on its capabilities and performance.