ValueError: Please set --model <model_id_or_path>`, model: None

[rahulverma7788]

!swift sft
--model_type got-ocr2
--model_id_or_path stepfun-ai/GOT-OCR2_0
--sft_type lora
--dataset /kaggle/working/converted_dataset.json

run sh: /opt/conda/bin/python3.10 /kaggle/working/ms-swift/swift/cli/sft.py --model_type got-ocr2 --model_id_or_path stepfun-ai/GOT-OCR2_0 --sft_type lora --dataset /kaggle/working/converted_dataset.json

[INFO:swift] Successfully registered /kaggle/working/ms-swift/swift/llm/dataset/data/dataset_info.json
[INFO:swift] Successfully registered []
[INFO:swift] rank: -1, local_rank: -1, world_size: 1, local_world_size: 1
Traceback (most recent call last):
File "/kaggle/working/ms-swift/swift/cli/sft.py", line 5, in
sft_main()
File "/kaggle/working/ms-swift/swift/llm/train/sft.py", line 308, in sft_main
return SwiftSft(args).main()
File "/kaggle/working/ms-swift/swift/llm/train/sft.py", line 31, in init
super().init(args)
File "/kaggle/working/ms-swift/swift/llm/base.py", line 18, in init
self.args = self._parse_args(args)
File "/kaggle/working/ms-swift/swift/llm/base.py", line 27, in _parse_args
args, remaining_argv = parse_args(self.args_class, args)
File "/kaggle/working/ms-swift/swift/utils/utils.py", line 146, in parse_args
args, remaining_args = parser.parse_args_into_dataclasses(argv, return_remaining_strings=True)
File "/opt/conda/lib/python3.10/site-packages/transformers/hf_argparser.py", line 339, in parse_args_into_dataclasses
obj = dtype(**inputs)
File "", line 266, in init
File "/kaggle/working/ms-swift/swift/llm/argument/train_args.py", line 128, in post_init
BaseArguments.post_init(self)
File "/kaggle/working/ms-swift/swift/llm/argument/base_args/base_args.py", line 87, in post_init
ModelArguments.post_init(self)
File "/kaggle/working/ms-swift/swift/llm/argument/base_args/model_args.py", line 123, in post_init
raise ValueError(f'Please set --model <model_id_or_path>, model: {self.model}') ValueError: Please set --model <model_id_or_path>, model: None

getting error during fine tuning, in the past this was working without any issues.

[rahulverma7788]

please help me.

[LukasDauterman]

I encountered this issue, it seems that there are undocumented changes in ms-swift here is what I had to do:

• changed --model_id_or_path to --model

There was a following error with --sft_type not being recognized at its due to the arg name being changed in the arg class used to parse the args:

• change --sft_type to --train_type

This has gotten me past the errors then it suggests running "pip install torchvision verovio" for GOT 2.0

[rahulverma7788]

Thanks, i will check it. i have another question, model is taking long inference time after training, can i reduce it? have you any idea about it?

[LukasDauterman]

Currently looking into that myself, I had found the vllm package did not work, and I am using the pt backend.

It looks like its runs all the inferences in a thread pool before it even outputs the results.

I think my solution for the time being is to make a small dataset to inference on, but then I need to figure out how to pass that to the inference script.

[LukasDauterman]

My work around was to write a jsonl with a handful of examples, then in the checkpoint args.json pointed the val_dataset to the new dataset.

[rahulverma7788]

In my case, I am predicting image-to-LaTeX, where the image contains table data. After training, it is taking too much time during inference and is also not handling complex tables effectively.