qlora_llama3_2_vision_11b

torchtune.models.llama3_2_vision.qlora_llama3_2_vision_11b(lora_attn_modules: List[Literal['q_proj', 'k_proj', 'v_proj', 'output_proj']], decoder_trainable: str = 'frozen', encoder_trainable: str = 'lora', fusion_trainable: str = 'lora', 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, image_size: int = 560) → DeepFusionModel

Builder for creating a Llama3.2 vision 11B 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_llama3_2_vision_11b for full API arguments.