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model:
arch: mini_gpt4_llama_v2
freeze_vit: True
freeze_qformer: True
max_txt_len: 256
low_resource: True
image_size: 224
end_sym: "</s>"
# 🔧 使用更小的模型以节省显存
llama_model: "microsoft/Phi-3.5-mini-instruct"
ckpt: "checkpoints/video_llama_checkpoint_last.pth"
use_grad_checkpoint: True
chat_template: True
lora_r: 64
lora_alpha: 16
length: 50
use_grad_checkpoint_llm: True
max_context_len: 3600
architectures: [
"MiniGPT4_Video"
]
device: "cuda"
drop_path_rate: 0
img_size: 224
model_type: "minigpt4_video"
num_query_token: 32
prompt: ""
# 🔧 使用float32以避免精度问题
torch_dtype: "float32"
transformers_version: "4.42.3"
vit_precision: "fp16"
vit_model: "eva_clip_g"
token_pooling: true
lora_target_modules : ["q_proj","v_proj"]
lora_dropout: 0.05
remove_template: false
prompt_path: ""
minigpt4_gpu_id: 0
whisper_gpu_id: 0
answer_module_gpu_id: 0
datasets:
video_chatgpt:
batch_size: 2 # 🔧 减小batch size以节省显存
vis_processor:
train:
name: "blip2_image_train"
image_size: 224
text_processor:
train:
name: "blip_caption"
sample_ratio: 200
run:
seed: 42
amp: false # 🔧 禁用AMP以避免兼容性问题 |