chore: import upstream snapshot with attribution
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This commit is contained in:
wehub-resource-sync
2026-07-13 13:34:58 +08:00
commit a203934033
1368 changed files with 175001 additions and 0 deletions
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CUDA_VISIBLE_DEVICES=0 \
VIDEO_MAX_PIXELS=50176 \
FPS_MAX_FRAMES=12 \
MAX_PIXELS=1003520 \
ENABLE_AUDIO_OUTPUT=0 \
swift infer \
--adapters output/vx-xxx/checkpoint-xxx \
--stream true \
--load_data_args true \
--max_new_tokens 2048
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# 4*35GB
# A demo for four modalities that can be run directly
nproc_per_node=4
# If using zero3, please set `ENABLE_AUDIO_OUTPUT=0`.
CUDA_VISIBLE_DEVICES=0,1,2,3 \
ENABLE_AUDIO_OUTPUT=1 \
NPROC_PER_NODE=$nproc_per_node \
VIDEO_MAX_PIXELS=50176 \
FPS_MAX_FRAMES=12 \
MAX_PIXELS=1003520 \
swift sft \
--model Qwen/Qwen2.5-Omni-7B \
--dataset 'AI-ModelScope/alpaca-gpt4-data-zh#2000' \
'AI-ModelScope/LaTeX_OCR:human_handwrite#2000' \
'speech_asr/speech_asr_aishell1_trainsets:validation#2000' \
'swift/VideoChatGPT:all#2000' \
--load_from_cache_file true \
--split_dataset_ratio 0.01 \
--tuner_type lora \
--torch_dtype bfloat16 \
--num_train_epochs 1 \
--per_device_train_batch_size 1 \
--per_device_eval_batch_size 1 \
--learning_rate 1e-4 \
--lora_rank 8 \
--lora_alpha 32 \
--target_modules all-linear \
--freeze_vit true \
--freeze_aligner true \
--gradient_accumulation_steps $(expr 16 / $nproc_per_node) \
--eval_steps 50 \
--save_steps 50 \
--save_total_limit 2 \
--logging_steps 5 \
--max_length 2048 \
--output_dir output \
--warmup_ratio 0.05 \
--dataloader_num_workers 4 \
--deepspeed zero2