Issues Converting lit_model.pth to Huggingface Format Using convert_from_litgpt

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Hello,

I have been using **litgpt** to pretrain a model, which produces a `lit_model.pth` file. This model functions correctly when loaded with `LLM.load()` for inference.

However, when I attempt to convert this model to the Huggingface format using the `convert_from_litgpt` script provided by litgpt, it outputs a `model.pth` file. This file doesn't meet Huggingface's expected format, and when I try to load it using Huggingface's tools, I receive the following error:
```python
state_dict = torch.load("model.pth")
model = AutoModel.from_pretrained(
model_id, local_files_only=True, state_dict=state_dict
)
```

```bash
OSError: Error no file named pytorch_model.bin, model.safetensors, tf_model.h5, model.ckpt.index or flax_model.msgpack found in directory
```

I am unsure how to resolve this issue. Is there a step I'm missing in the conversion process, or is there a compatibility issue with the `convert_from_litgpt` script?

Additionally, I noticed that the `.pth` file obtained after training with lit-gpt is twice the size of the original model. Could you please explain why this is happening?

Thank you for your assistance.

Start by reproducing the conversion with the mentioned `lit_model.pth` and `convert_from_litgpt` script, then inspect the resulting `model.pth` against the Hugging Face loading snippet and reported filename error. Determine whether the conversion output is accepted by Hugging Face and document or correct the handling of the converted file; also investigate why the post-training `.pth` file is twice the original size.

Written by the indexing model from the issue text.