文件列表:

assets/
src/
LICENSE
app.py
app_mm.py
database.csv
input.csv
requirements.txt

# ion

This is a simple utility designed using the Streamlit library to facilitate the creation and annotation of instruction tuning datasets using multiple modalities. The tool allows you to import a folder containing the content you want to annotate and provides an easy-to-use interface for labeling. ## Features - **Multi-Modality Support:** Annotate datasets with multiple modalities, such as text, image, audio & video. - **Folder & CSV File Import:** Import your data/prompts from a CSV file or a folder. CSV file import is only supported for text data. ## Installation 1. Clone this repository: ```bash git clone https://github.com/vijpandaturtle/instruction-tuner.git cd instruction-tuner ``` 2. Install the required dependencies: ```bash pip install -r requirements.txt ``` ## Usage 1. Run the application (for text only): ```bash streamlit run app.py ``` For multimodal support ```bash streamlit run app_mm.py ``` 2. Open the provided URL in your web browser. 3. Select your data source from the dropdown on the sidebar. 4. Specify the folder path, and start annotating! ## Contributing Contributions are welcome! Simply make a pull request with the feature you are planning to add! ## Contact For questions or feedback, please contact thisisvij98@gmail.com.

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