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Use PEFT or Full-parameter to finetune 300+ LLMs or 80+ MLLMs. (Qwen2, GLM4v, Internlm2.5, Yi, Llama3.1, Llava-Video, Internvl2, MiniCPM-V-2.6, Deepseek, Baichuan2, Gemma2, Phi3-Vision, ...)
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ImportError: cannot import name 'LlavaOnevisionForConditionalGeneration' from 'transformers' #1878

Closed Lopa07 closed 1 week ago

Lopa07 commented 2 weeks ago

Describe the bug I am trying to SFT fine-tune the model llava-onevision-qwen2-0_5b-ov using the following command:

swift sft \
    --model_type llava-onevision-qwen2-0_5b-ov \
    --dataset rlaif-v#1000 \
    --dataset_test_ratio 0.1 \
    --num_train_epochs 5 \
    --output_dir output

I received the error, ImportError: cannot import name 'LlavaOnevisionForConditionalGeneration' from 'transformers'. The error message along with the complete stack is posted below.

(swift) m.banerjee@PHYVDGPU02PRMV:/VDIL_COREML/m.banerjee/ms-swift$ CUDA_VISIBLE_DEVICES=0,1,2,3,5 \
swift sft \
    --model_type llava-onevision-qwen2-0_5b-ov \
    --dataset rlaif-v#1000 \
    --dataset_test_ratio 0.1 \
    --num_train_epochs 5 \
    --output_dir output

run sh: `/VDIL_COREML/m.banerjee/anaconda3/envs/swift/bin/python /VDIL_COREML/m.banerjee/ms-swift/swift/cli/sft.py --model_type llava-onevision-qwen2-0_5b-ov --dataset rlaif-v#1000 --dataset_test_ratio 0.1 --num_train_epochs 5 --output_dir output`
[INFO:swift] Successfully registered `/VDIL_COREML/m.banerjee/ms-swift/swift/llm/data/dataset_info.json`
[INFO:swift] No vLLM installed, if you are using vLLM, you will get `ImportError: cannot import name 'get_vllm_engine' from 'swift.llm'`
[INFO:swift] No LMDeploy installed, if you are using LMDeploy, you will get `ImportError: cannot import name 'prepare_lmdeploy_engine_template' from 'swift.llm'`
[INFO:swift] Start time of running main: 2024-08-31 01:32:33.881287
[INFO:swift] Setting template_type: llava-onevision-qwen
[INFO:swift] Setting args.lazy_tokenize: True
[INFO:swift] Setting args.dataloader_num_workers: 1
[INFO:swift] output_dir: /VDIL_COREML/m.banerjee/ms-swift/output/llava-onevision-qwen2-0_5b-ov/v0-20240831-013234
[INFO:swift] args: SftArguments(model_type='llava-onevision-qwen2-0_5b-ov', model_id_or_path='AI-ModelScope/llava-onevision-qwen2-0.5b-ov-hf', model_revision='master', full_determinism=False, sft_type='lora', freeze_parameters=0.0, additional_trainable_parameters=[], tuner_backend='peft', template_type='llava-onevision-qwen', output_dir='/VDIL_COREML/m.banerjee/ms-swift/output/llava-onevision-qwen2-0_5b-ov/v0-20240831-013234', add_output_dir_suffix=True, ddp_backend=None, ddp_find_unused_parameters=None, ddp_broadcast_buffers=None, seed=42, resume_from_checkpoint=None, resume_only_model=False, ignore_data_skip=False, dtype='bf16', packing=False, train_backend='transformers', tp=1, pp=1, min_lr=None, sequence_parallel=False, dataset=['rlaif-v#1000'], val_dataset=[], dataset_seed=42, dataset_test_ratio=0.1, use_loss_scale=False, loss_scale_config_path='/VDIL_COREML/m.banerjee/ms-swift/swift/llm/agent/default_loss_scale_config.json', system=None, tools_prompt='react_en', max_length=2048, truncation_strategy='delete', check_dataset_strategy='none', streaming=False, streaming_val_size=0, streaming_buffer_size=16384, model_name=[None, None], model_author=[None, None], quant_method=None, quantization_bit=0, hqq_axis=0, hqq_dynamic_config_path=None, bnb_4bit_comp_dtype='bf16', bnb_4bit_quant_type='nf4', bnb_4bit_use_double_quant=True, bnb_4bit_quant_storage=None, rescale_image=-1, target_modules='^(language_model|multi_modal_projector)(?!.*(lm_head|output|emb|wte|shared)).*', target_regex=None, modules_to_save=[], lora_rank=8, lora_alpha=32, lora_dropout=0.05, lora_bias_trainable='none', lora_dtype='AUTO', lora_lr_ratio=None, use_rslora=False, use_dora=False, init_lora_weights='true', fourier_n_frequency=2000, fourier_scaling=300.0, rope_scaling=None, boft_block_size=4, boft_block_num=0, boft_n_butterfly_factor=1, boft_dropout=0.0, vera_rank=256, vera_projection_prng_key=0, vera_dropout=0.0, vera_d_initial=0.1, adapter_act='gelu', adapter_length=128, use_galore=False, galore_target_modules=None, galore_rank=128, galore_update_proj_gap=50, galore_scale=1.0, galore_proj_type='std', galore_optim_per_parameter=False, galore_with_embedding=False, galore_quantization=False, galore_proj_quant=False, galore_proj_bits=4, galore_proj_group_size=256, galore_cos_threshold=0.4, galore_gamma_proj=2, galore_queue_size=5, adalora_target_r=8, adalora_init_r=12, adalora_tinit=0, adalora_tfinal=0, adalora_deltaT=1, adalora_beta1=0.85, adalora_beta2=0.85, adalora_orth_reg_weight=0.5, ia3_feedforward_modules=[], llamapro_num_new_blocks=4, llamapro_num_groups=None, neftune_noise_alpha=None, neftune_backend='transformers', lisa_activated_layers=0, lisa_step_interval=20, reft_layers=None, reft_rank=4, reft_intervention_type='LoreftIntervention', reft_args=None, gradient_checkpointing=True, deepspeed=None, batch_size=1, eval_batch_size=1, auto_find_batch_size=False, num_train_epochs=5, max_steps=-1, optim='adamw_torch', adam_beta1=0.9, adam_beta2=0.95, adam_epsilon=1e-08, learning_rate=0.0001, weight_decay=0.1, gradient_accumulation_steps=16, max_grad_norm=1, predict_with_generate=False, lr_scheduler_type='cosine', lr_scheduler_kwargs={}, warmup_ratio=0.05, warmup_steps=0, eval_steps=50, save_steps=50, save_only_model=False, save_total_limit=2, logging_steps=5, acc_steps=1, dataloader_num_workers=1, dataloader_pin_memory=True, dataloader_drop_last=False, push_to_hub=False, hub_model_id=None, hub_token=None, hub_private_repo=False, push_hub_strategy='push_best', test_oom_error=False, disable_tqdm=False, lazy_tokenize=True, preprocess_num_proc=1, use_flash_attn=None, ignore_args_error=False, check_model_is_latest=True, logging_dir='/VDIL_COREML/m.banerjee/ms-swift/output/llava-onevision-qwen2-0_5b-ov/v0-20240831-013234/runs', report_to=['tensorboard'], acc_strategy='token', save_on_each_node=False, evaluation_strategy='steps', save_strategy='steps', save_safetensors=True, gpu_memory_fraction=None, include_num_input_tokens_seen=False, local_repo_path=None, custom_register_path=None, custom_dataset_info=None, device_map_config_path=None, device_max_memory=[], max_new_tokens=2048, do_sample=True, temperature=0.3, top_k=20, top_p=0.7, repetition_penalty=1.0, num_beams=1, fsdp='', fsdp_config=None, sequence_parallel_size=1, model_layer_cls_name=None, metric_warmup_step=0, fsdp_num=1, per_device_train_batch_size=None, per_device_eval_batch_size=None, eval_strategy=None, self_cognition_sample=0, train_dataset_mix_ratio=0.0, train_dataset_mix_ds=['ms-bench'], train_dataset_sample=-1, val_dataset_sample=None, safe_serialization=None, only_save_model=None, neftune_alpha=None, deepspeed_config_path=None, model_cache_dir=None, lora_dropout_p=None, lora_target_modules=[], lora_target_regex=None, lora_modules_to_save=[], boft_target_modules=[], boft_modules_to_save=[], vera_target_modules=[], vera_modules_to_save=[], ia3_target_modules=[], ia3_modules_to_save=[], custom_train_dataset_path=[], custom_val_dataset_path=[])
[INFO:swift] Global seed set to 42
device_count: 5
rank: -1, local_rank: -1, world_size: 1, local_world_size: 1
[INFO:swift] Downloading the model from ModelScope Hub, model_id: AI-ModelScope/llava-onevision-qwen2-0.5b-ov-hf
[WARNING:modelscope] Using branch: master as version is unstable, use with caution
[INFO:swift] Loading the model using model_dir: /VDIL_COREML/m.banerjee/.cache/modelscope/hub/AI-ModelScope/llava-onevision-qwen2-0___5b-ov-hf
Traceback (most recent call last):
  File "/VDIL_COREML/m.banerjee/ms-swift/swift/cli/sft.py", line 5, in <module>
    sft_main()
  File "/VDIL_COREML/m.banerjee/ms-swift/swift/utils/run_utils.py", line 32, in x_main
    result = llm_x(args, **kwargs)
  File "/VDIL_COREML/m.banerjee/ms-swift/swift/llm/sft.py", line 215, in llm_sft
    model, tokenizer = get_model_tokenizer(
  File "/VDIL_COREML/m.banerjee/ms-swift/swift/llm/utils/model.py", line 6347, in get_model_tokenizer
    model, tokenizer = get_function(model_dir, torch_dtype, model_kwargs, load_model, **kwargs)
  File "/VDIL_COREML/m.banerjee/ms-swift/swift/llm/utils/model.py", line 5889, in get_model_tokenizer_llava_onevision
    from transformers import LlavaOnevisionForConditionalGeneration
ImportError: cannot import name 'LlavaOnevisionForConditionalGeneration' from 'transformers' (/VDIL_COREML/m.banerjee/anaconda3/envs/swift/lib/python3.9/site-packages/transformers/__init__.py)
(swift) m.banerjee@PHYVDGPU02PRMV:/VDIL_COREML/m.banerjee/ms-swift$

Your hardware and system info CUDA Version: 12.4 System: Ubuntu 22.04.3 LTS GPU torch==2.4.0 transformers==4.45.0.dev0 trl==0.9.6 peft==0.12.0

Jintao-Huang commented 2 weeks ago

Please pay attention to this PR: https://github.com/huggingface/transformers/pull/32673

Lopa07 commented 2 weeks ago

Thank you @Jintao-Huang! I am waiting till the branch zucchini-nlp:llava-onevision for the ^ PR is merged. Then I can test and close this issue.

Lopa07 commented 1 week ago

The PR has merged.