## Data We have open-sourced our dataset of 32,555 pairs, which includes Chinese data. The dataset is available [here](https://huggingface.co/datasets/LanguageBind/Open-Sora-Plan-v1.3.0/tree/main/prompt_refiner). The details can be found [here](https://github.com/PKU-YuanGroup/Open-Sora-Plan/blob/main/docs/Report-v1.3.0.md#prompt-refiner). In fact, it is a JSON file with the following structure. ``` [ { "instruction": "Refine the sentence: \"A newly married couple sharing a piece of there wedding cake.\" to contain subject description, action, scene description. (Optional: camera language, light and shadow, atmosphere) and conceive some additional actions to make the sentence more dynamic. Make sure it is a fluent sentence, not nonsense.", "input": "", "output": "The newlywed couple, dressed in elegant attire..." }, ... ] ``` ## Train `--data_path` is the path to the prepared JSON file. `--model_path` is the directory containing the LLaMA 3.1 weights, including `config.json` and some weight files. `--lora_out_path` is the path where the LoRA model will be saved. ``` cd opensora/models/prompt_refiner CUDA_VISIBLE_DEVICES=0 python train.py \ --data_path path/to/data.json \ --model_path path/to/llama_model \ --lora_out_path path/to/save/lora_model ``` ## Merge `--model_path` is the directory containing the LLaMA 3.1 weights, including `config.json` and some weight files. `--lora_in_path` is the directory containing the pre-trained LoRA model. `--lora_out_path` is the path for the merged model. ``` cd opensora/models/prompt_refiner CUDA_VISIBLE_DEVICES=0 python merge.py \ --base_path path/to/llama_model \ --lora_in_path path/to/save/lora_model \ --lora_out_path path/to/save/merge_model ``` ## Inference `--model_path` is the directory containing the weights (LLaMA 3.1 or merged Lora weight), including `config.json` and some weight files. `--prompt` is the text you want to input, which will be refined. ``` cd opensora/models/prompt_refiner CUDA_VISIBLE_DEVICES=0 python merge.py \ --mode_path path/to/data.json \ --prompt path/to/save/lora_model ```