CCL2023 Demo
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model training
torchrun --nproc_per_node=8 \ --master_port=1234 baichuan_instruction_generation.py \ --model_name_or_path baichuan-inc/Baichuan-7B \ --data_path $DATA_PATH \ --output_dir $OUTPUT_PATH \ --num_train_epochs 3 \ --per_device_train_batch_size 4 \ --per_device_eval_batch_size 4 \ --gradient_accumulation_steps 4 \ --evaluation_strategy "no" \ --save_strategy "steps" \ --save_steps 2000 \ --save_total_limit 1 \ --learning_rate 2e-5 \ --weight_decay 0. \ --warmup_ratio 0.03 \ --lr_scheduler_type "cosine" \ --logging_steps 1 \ --fp16 True \ --report_to 'none' -
model inference
for template_id in {0,1,2} do python baichuan_generation.py \ --base_model $MODEL_DIR \ --tokenizer_path baichuan-inc/Baichuan-7B \ --data_file $DATA_FILE \ --with_prompt \ --predictions_file $PREDICTIONS_FILE \ --template_id ${template_id} \ done -
demo
python demo.py