KoLLaVA : Korean Large Language and Vision Assistant (feat. LLaVA)
This model is a large multimodal model (LMM) that combines the LLM(LLaMA-2-7b-ko) with visual encoder of CLIP(ViT-14), trained on Korean visual-instruction dataset using QLoRA.
Detail codes are available at KoLLaVA github repository
- Training hyperparameters
- learning rate : 2e-4
- train_batch_size: 16
- distributed_type: multi-GPU (RTX3090 24G)
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 4
- lr_scheduler_type: cosine
- num_epochs: 1
- lora_enable: True
- bits: 4
Model License: cc-by-nc-4.0
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