Error finetuning - OpenGVLab/Mini-InternVL-Chat-4B-V1-5 does not exist

[babla9]

Describe the bug What the bug is, and how to reproduce, better with screenshots(描述bug以及复现过程，最好有截图)

Thanks so much for your work on this project, I'm trying to finetune the mini-internvl-v1.5 and it looks like its unable to find the model. Let me know what I should change to address this, thanks! Do you also happen to know how much GPU memory is required to train this model?

CUDA_VISIBLE_DEVICES=0,1 swift sft --model_type mini-internvl-chat-4b-v1_5 --dataset train_test.jsonl

[INFO:swift] args: SftArguments(model_type='mini-internvl-chat-4b-v1_5', model_id_or_path='OpenGVLab/Mini-InternVL-Chat-4B-V1-5', model_revision='master', sft_type='lora', freeze_parameters=0.0, additional_trainable_parameters=[], tuner_backend='peft', template_type='internvl-phi3', output_dir='/home/ubuntu/swift/output/mini-internvl-chat-4b-v1_5/v1-20240701-154202', 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, dataset=['final_datasets/merged_reddit_sephora/output_data/image_only_merged_default_format.json'], val_dataset=[], dataset_seed=42, dataset_test_ratio=0.01, use_loss_scale=False, loss_scale_config_path='/home/ubuntu/swift/swift/llm/agent/default_loss_scale_config.json', system=None, tools_prompt='react_en', max_length=4096, truncation_strategy='delete', check_dataset_strategy='none', 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, lora_target_modules=['qkv_proj'], lora_rank=8, lora_alpha=32, lora_dropout_p=0.05, lora_bias_trainable='none', lora_modules_to_save=[], lora_dtype='AUTO', lora_lr_ratio=None, use_rslora=False, use_dora=False, init_lora_weights='true', rope_scaling=None, boft_block_size=4, boft_block_num=0, boft_n_butterfly_factor=1, boft_target_modules=['DEFAULT'], boft_dropout=0.0, boft_modules_to_save=[], vera_rank=256, vera_target_modules=['DEFAULT'], vera_projection_prng_key=0, vera_dropout=0.0, vera_d_initial=0.1, vera_modules_to_save=[], adapter_act='gelu', adapter_length=128, use_galore=False, galore_rank=128, galore_target_modules=None, galore_update_proj_gap=50, galore_scale=1.0, galore_proj_type='std', galore_optim_per_parameter=False, galore_with_embedding=False, 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_target_modules=['DEFAULT'], ia3_feedforward_modules=[], ia3_modules_to_save=[], llamapro_num_new_blocks=4, llamapro_num_groups=None, neftune_noise_alpha=None, neftune_backend='transformers', lisa_activated_layers=0, lisa_step_interval=20, gradient_checkpointing=True, deepspeed=None, batch_size=1, eval_batch_size=1, num_train_epochs=1, max_steps=-1, optim='adamw_torch', adam_beta1=0.9, adam_beta2=0.999, adam_epsilon=1e-08, learning_rate=0.0001, weight_decay=0.1, gradient_accumulation_steps=16, max_grad_norm=0.5, predict_with_generate=False, lr_scheduler_type='linear', warmup_ratio=0.05, eval_steps=50, save_steps=50, save_only_model=False, save_total_limit=2, logging_steps=5, acc_steps=1, dataloader_num_workers=0, dataloader_pin_memory=False, 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='/home/ubuntu/swift/output/mini-internvl-chat-4b-v1_5/v1-20240701-154202/runs', report_to=['tensorboard'], acc_strategy='token', save_on_each_node=True, 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, 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, custom_train_dataset_path=[], custom_val_dataset_path=[])
[INFO:swift] Global seed set to 42
device_count: 2
rank: -1, local_rank: -1, world_size: 1, local_world_size: 1
[INFO:swift] Downloading the model from ModelScope Hub, model_id: OpenGVLab/Mini-InternVL-Chat-4B-V1-5
[ERROR:modelscope] The request model: OpenGVLab/Mini-InternVL-Chat-4B-V1-5 does not exist!
Traceback (most recent call last):
  File "/home/ubuntu/swift/swift/cli/sft.py", line 5, in <module>
    sft_main()
  File "/home/ubuntu/swift/swift/utils/run_utils.py", line 27, in x_main
    result = llm_x(args, **kwargs)
  File "/home/ubuntu/swift/swift/llm/sft.py", line 107, in llm_sft
    model, tokenizer = get_model_tokenizer(
  File "/home/ubuntu/swift/swift/llm/utils/model.py", line 5189, in get_model_tokenizer
    model_dir = safe_snapshot_download(
  File "/home/ubuntu/swift/swift/llm/utils/model.py", line 5154, in safe_snapshot_download
    model_dir = snapshot_download(model_id_or_path, revision, ignore_file_pattern=ignore_file_pattern)
  File "/opt/conda/envs/swift-env/lib/python3.10/site-packages/modelscope/hub/snapshot_download.py", line 94, in snapshot_download
    revision_detail = _api.get_valid_revision_detail(
  File "/opt/conda/envs/swift-env/lib/python3.10/site-packages/modelscope/hub/api.py", line 499, in get_valid_revision_detail
    all_branches_detail, all_tags_detail = self.get_model_branches_and_tags_details(
  File "/opt/conda/envs/swift-env/lib/python3.10/site-packages/modelscope/hub/api.py", line 579, in get_model_branches_and_tags_details
    handle_http_response(r, logger, cookies, model_id)
  File "/opt/conda/envs/swift-env/lib/python3.10/site-packages/modelscope/hub/errors.py", line 117, in handle_http_response
    raise HTTPError(http_error_msg, response=response)
requests.exceptions.HTTPError: The request model: OpenGVLab/Mini-InternVL-Chat-4B-V1-5 does not exist!

Your hardware and system info Write your system info like CUDA version/system/GPU/torch version here(在这里给出硬件信息和系统信息，如CUDA版本，系统，GPU型号和torch版本等)

Additional context Add any other context about the problem here(在这里补充其他信息)

[Jintao-Huang]

USE_HF=1 CUDA_VISIBLE_DEVICES=0,1 swift sft --model_type mini-internvl-chat-4b-v1_5 --dataset train_test.jsonl

[LiJunY]

指定 --model_id_or_path 补充模型路径[mini4b]

[babla9]

thanks to you both!