感谢您的精彩项目。我复制了FinGPT v3.1.2(4位QLORA)。它可以在Colab上的默认LLM模型“chatglm2”上工作，但当我想要使用Llama2获得更好的结果时，它会停止运行。

• 我根据您的指示更改了模型，将model_name = "THUDM/chatglm2-6b"更改为model_name = "daryl149/llama-2-7b-chat-hf"
• 然后由于运行错误删除了设备：

model = AutoModel.from_pretrained(
        model_name,
        quantization_config=q_config,
        trust_remote_code=True,
        token = access_token,
        # device='cuda'
    )

• 将target_modules更改为llama:

target_modules = TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING['llama']

• 不幸的是，最后一步出现了一个TypeError: 'NoneType' object cannot be interpreted as an integer

writer = SummaryWriter()
trainer = ModifiedTrainer(
    model=model,
    args=training_args,             # Trainer args
    train_dataset=dataset["train"], # Training set
    eval_dataset=dataset["test"],   # Testing set
    data_collator=data_collator,    # Data Collator
    callbacks=[TensorBoardCallback(writer)],
)
trainer.train()
writer.close()
# save model
model.save_pretrained(training_args.output_dir)

详细的错误如下：

You are adding a <class 'transformers.integrations.TensorBoardCallback'> to the callbacks of this Trainer, but there is already one. The currentlist of callbacks is
:DefaultFlowCallback
TensorBoardCallback
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-27-d05cf508c134> in <cell line: 11>()
      9     callbacks=[TensorBoardCallback(writer)],
     10 )
---> 11 trainer.train()
     12 writer.close()
     13 # save model
6 frames
<ipython-input-25-26476d7038e4> in data_collator(features)
     37         ids = ids + [tokenizer.pad_token_id] * (longest - ids_l)
     38         _ids = torch.LongTensor(ids)
---> 39         labels_list.append(torch.LongTensor(labels))
     40         input_ids.append(_ids)
     41     input_ids = torch.stack(input_ids)
TypeError: 'NoneType' object cannot be interpreted as an integer

您能帮我解决这个问题吗？期待您的回复！(平台：Google Colab上的A100)