Instructions to use googcheng/7b-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use googcheng/7b-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("baichuan-inc/Baichuan-7B") model = PeftModel.from_pretrained(base_model, "googcheng/7b-lora") - Notebooks
- Google Colab
- Kaggle
模型功能: 古诗句接龙 based on baichuan-inc/Baichuan-7B
Training procedure
CUDA_VISIBLE_DEVICES=0 python src/train_bash.py --stage sft --model_name_or_path baichuan-inc/Baichuan-7B --do_train --dataset alpaca_gpt4_zh --template default --finetuning_type lora --output_dir path_to_sft_checkpoint --overwrite_cache --per_device_train_batch_size 4 --gradient_accumulation_steps 4 --lr_scheduler_type cosine --logging_steps 10 --save_steps 1000 --learning_rate 5e-5 --num_train_epochs 20 --plot_loss --fp16 --lora_target W_pack
Framework versions
- PEFT 0.4.0
Test
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