Package Installation Problems

[SidUParis]

(Windows Py3.9)

(labsession) D:\PYTHON\git_llmtuner\LLMTuner>pip3 install git+https://github.com/promptslab/LLMTuner
Collecting git+https://github.com/promptslab/LLMTuner
  Cloning https://github.com/promptslab/LLMTuner to c:\users\luxury\appdata\local\temp\pip-req-build-2sdv2jxy
  Running command git clone --filter=blob:none --quiet https://github.com/promptslab/LLMTuner 'C:\Users\luxury\AppData\Local\Temp\pip-req-build-2sdv2jxy'
  Resolved https://github.com/promptslab/LLMTuner to commit 470be41ad646d205973bd40b80cabe54d4934559
  Preparing metadata (setup.py) ... error
  error: subprocess-exited-with-error

  × python setup.py egg_info did not run successfully.
  │ exit code: 1
  ╰─> [6 lines of output]
      Traceback (most recent call last):
        File "<string>", line 2, in <module>
        File "<pip-setuptools-caller>", line 34, in <module>
        File "C:\Users\luxury\AppData\Local\Temp\pip-req-build-2sdv2jxy\setup.py", line 9, in <module>
          long_description=open('README.md').read(),
      UnicodeDecodeError: 'gbk' codec can't decode byte 0xa4 in position 2218: illegal multibyte sequence
      [end of output]

  note: This error originates from a subprocess, and is likely not a problem with pip.
error: metadata-generation-failed

× Encountered error while generating package metadata.
╰─> See above for output.

note: This is an issue with the package mentioned above, not pip.
hint: See above for details.

[notice] A new release of pip is available: 23.3.1 -> 24.0
[notice] To update, run: python.exe -m pip install --upgrade pip

To solve this, only method is to clone the repo to the local directory, then modify the setup.py, for the line:

long_description=open('README.md', encoding='utf-8').read(),

Then in CMD use

Python setup.py install

---

After this installation, there are some problems when using the package.

1. lack of necessary packages such as starlette,toolz,llvmlite,etc.
2. tuner.fit() cannot work with errors:

trainable params: 3,538,944 || all params: 245,273,856 || trainable%: 1.442854145857274
None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[9], [line 3](vscode-notebook-cell:?execution_count=9&line=3)
      [1](vscode-notebook-cell:?execution_count=9&line=1) tuner = Tuner(model,dataset)
----> [3](vscode-notebook-cell:?execution_count=9&line=3) trained_model = tuner.fit()

File [d:\PYTHON\ENV\labsession\lib\site-packages\llmtuner-0.1.0-py3.10.egg\llmtuner\tuner\whisper_tuner.py:30](file:///D:/PYTHON/ENV/labsession/lib/site-packages/llmtuner-0.1.0-py3.10.egg/llmtuner/tuner/whisper_tuner.py:30), in Tuner.fit(self)
     [28](file:///D:/PYTHON/ENV/labsession/lib/site-packages/llmtuner-0.1.0-py3.10.egg/llmtuner/tuner/whisper_tuner.py:28)     trainer.setup_trainer(self.training_args_dict)
     [29](file:///D:/PYTHON/ENV/labsession/lib/site-packages/llmtuner-0.1.0-py3.10.egg/llmtuner/tuner/whisper_tuner.py:29) else:
---> [30](file:///D:/PYTHON/ENV/labsession/lib/site-packages/llmtuner-0.1.0-py3.10.egg/llmtuner/tuner/whisper_tuner.py:30)     trainer.setup_trainer()
     [32](file:///D:/PYTHON/ENV/labsession/lib/site-packages/llmtuner-0.1.0-py3.10.egg/llmtuner/tuner/whisper_tuner.py:32) # Start the training process
     [33](file:///D:/PYTHON/ENV/labsession/lib/site-packages/llmtuner-0.1.0-py3.10.egg/llmtuner/tuner/whisper_tuner.py:33) trainer.start_training()

File [d:\PYTHON\ENV\labsession\lib\site-packages\llmtuner-0.1.0-py3.10.egg\llmtuner\trainer\whisper_trainer.py:76](file:///D:/PYTHON/ENV/labsession/lib/site-packages/llmtuner-0.1.0-py3.10.egg/llmtuner/trainer/whisper_trainer.py:76), in WhisperModelTrainer.setup_trainer(self, training_args_dict)
     [73](file:///D:/PYTHON/ENV/labsession/lib/site-packages/llmtuner-0.1.0-py3.10.egg/llmtuner/trainer/whisper_trainer.py:73) def setup_trainer(self, training_args_dict=None):
     [74](file:///D:/PYTHON/ENV/labsession/lib/site-packages/llmtuner-0.1.0-py3.10.egg/llmtuner/trainer/whisper_trainer.py:74)     # Define default arguments for training
---> [76](file:///D:/PYTHON/ENV/labsession/lib/site-packages/llmtuner-0.1.0-py3.10.egg/llmtuner/trainer/whisper_trainer.py:76)     training_args = Seq2SeqTrainingArguments(**training_args_dict)
     [77](file:///D:/PYTHON/ENV/labsession/lib/site-packages/llmtuner-0.1.0-py3.10.egg/llmtuner/trainer/whisper_trainer.py:77)     # Customize the training arguments based on the type of model
     [78](file:///D:/PYTHON/ENV/labsession/lib/site-packages/llmtuner-0.1.0-py3.10.egg/llmtuner/trainer/whisper_trainer.py:78)     if self.model.is_peft_applied:
     [79](file:///D:/PYTHON/ENV/labsession/lib/site-packages/llmtuner-0.1.0-py3.10.egg/llmtuner/trainer/whisper_trainer.py:79)         # Settings specific to PEFT model

TypeError: transformers.training_args_seq2seq.Seq2SeqTrainingArguments() argument after ** must be a mapping, not NoneType

The code used are from tutorial colab, but because of this step, I cannot proceed anymore.