docs: add Qwen3.8 LlamaFactory SFT skill (#10901)

Co-authored-by: Claude Opus 5 <noreply@anthropic.com>
This commit is contained in:
Cui-yshoho
2026-11-04 20:39:18 +08:00
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parent a3e7f60ae6
commit 84024cefa6
12 changed files with 702 additions and 0 deletions

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compute_environment: LOCAL_MACHINE
debug: false
distributed_type: FSDP
downcast_bf16: 'no'
fsdp_config:
fsdp_version: 2
fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
fsdp_transformer_layer_cls_to_wrap: Qwen3_5DecoderLayer,Qwen3_5VisionBlock
fsdp_cpu_ram_efficient_loading: true
fsdp_offload_params: false
fsdp_reshard_after_forward: true
fsdp_state_dict_type: FULL_STATE_DICT
machine_rank: 0
main_training_function: main
mixed_precision: bf16
num_machines: 1
num_processes: 16 # Change together with the visible-device list for your hardware.
rdzv_backend: static
same_network: true
use_cpu: false

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# Start HyperParallel FSDP2 full fine-tuning on Ascend NPU
# Usage:
# ASCEND_RT_VISIBLE_DEVICES=0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15 accelerate launch \
# --config_file examples/accelerate/fsdp2_config_qwen38.yaml \
# src/train.py examples/ascend/qwen3_8_full_sft_hyper_fsdp2.yaml
#
# Note: Change both the visible-device list and `num_processes` for your hardware.
### model
model_name_or_path: Qwen/Qwen3.8-27B
trust_remote_code: true
use_v1_kernels: true
flash_attn: fa2
### method
stage: sft
do_train: true
finetuning_type: full
use_hyper_parallel: true
### dataset
dataset: alpaca_en_demo
template: qwen3_8
cutoff_len: 2048
max_samples: 1000
overwrite_cache: true
preprocessing_num_workers: 16
dataloader_num_workers: 4
### output
output_dir: saves/Qwen3.8-27B/full/sft
logging_steps: 1
save_steps: 500
max_steps: 500
plot_loss: true
overwrite_output_dir: true
save_only_model: false
report_to: none # choices: [none, wandb, tensorboard, swanlab, mlflow]
### train
per_device_train_batch_size: 1
gradient_accumulation_steps: 1
learning_rate: 1.0e-5
lr_scheduler_type: cosine
warmup_ratio: 0.1
bf16: true
ddp_timeout: 1800
resume_from_checkpoint: null