yunjae-won/mpq3_llama8b_sft_dpo_beta1e-1_step1280
The yunjae-won/mpq3_llama8b_sft_dpo_beta1e-1_step1280 is an 8 billion parameter language model. 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 that more information is needed regarding its development, training, and intended applications.
Loading preview...
Model Overview
This model, yunjae-won/mpq3_llama8b_sft_dpo_beta1e-1_step1280, is an 8 billion parameter language model. The naming convention suggests it has undergone a training process involving Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO), likely building upon a Llama-based architecture. The model card indicates that further details regarding its development, specific capabilities, and training data are currently pending.
Key Characteristics
- Parameter Count: 8 billion parameters.
- Training Method: Implies Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO).
- Context Length: 8192 tokens.
Current Status
As per the provided model card, significant information is marked as "More Information Needed," including:
- Model developer and funding.
- Specific model type and language(s).
- License details.
- Details on direct and downstream uses.
- Bias, risks, and limitations.
- Training data and procedure.
- Evaluation metrics and results.
Recommendations
Users are advised to be aware of the current lack of detailed information regarding this model's specific performance, biases, and intended applications. Further recommendations will be available once more comprehensive model details are provided.