qlora_llama2_reward_7b

torchtune.models.llama2.qlora_llama2_reward_7b(lora_attn_modules: List[Literal['q_proj', 'k_proj', 'v_proj', 'output_proj']], apply_lora_to_mlp: bool = False, apply_lora_to_output: bool = False, lora_rank: int = 8, lora_alpha: float = 16, lora_dropout: float = 0.0, use_dora: bool = False, *, quantize_base: bool = True) → TransformerDecoder

Builder for creating a Llama2 reward 7b model with QLoRA enabled. Base model weights in linear layers that LoRA is applied to are quantized per the QLoRA paper: https://arxiv.org/abs/2305.14314. Please see lora_llama2_reward_7b for full API arguments.