FAMMA is a multi-modal financial Q&A benchmark dataset. The questions encompass three heterogeneous image types - tables, charts and text & math screenshots - and span eight subfields in finance, comprehensively covering topics across major asset classes. Additionally, all the questions are categorized by three difficulty levels — easy, medium, and hard - and are available in three languages — English, Chinese, and French. Furthermore, the questions are divided into two… See the full description on the dataset page:
https://huggingface.co/datasets/weaverbirdllm/famma.
