add nf4 qlora support on Ascend NPU (#6601)

* add nf4 qlora support on Ascend NPU

* add transformers version check

* add python>=3.10 requirement description for npu

* tiny fix

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Co-authored-by: hoshi-hiyouga <hiyouga@buaa.edu.cn>
Former-commit-id: 7912d1acac5f10dab22145fe729a90c57aad8d85
This commit is contained in:
codingma
2025-01-13 19:43:36 +08:00
committed by GitHub
parent 73c1c15b62
commit 11c38b9173
4 changed files with 104 additions and 10 deletions

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### model
model_name_or_path: meta-llama/Meta-Llama-3-8B-Instruct
quantization_bit: 4
quantization_method: bitsandbytes # choices: [bitsandbytes (4/8), hqq (2/3/4/5/6/8), eetq (8)]
double_quantization: false
trust_remote_code: true
### method
stage: sft
do_train: true
finetuning_type: lora
lora_target: all
### dataset
dataset: identity,alpaca_en_demo
template: llama3
cutoff_len: 2048
max_samples: 1000
overwrite_cache: true
preprocessing_num_workers: 16
### output
output_dir: saves/llama3-8b/lora/sft
logging_steps: 10
save_steps: 500
plot_loss: true
overwrite_output_dir: true
### train
per_device_train_batch_size: 1
gradient_accumulation_steps: 8
learning_rate: 1.0e-4
num_train_epochs: 3.0
lr_scheduler_type: cosine
warmup_ratio: 0.1
bf16: true
ddp_timeout: 180000000
### eval
val_size: 0.1
per_device_eval_batch_size: 1
eval_strategy: steps
eval_steps: 500