--- inference: false pipeline_tag: image-text-to-text ---

# Finedefics Model Card ## Model details **Model type:** Finedefics is an open-source MLLM that enhances the model's FGVR capability by incorporating informative attribute descriptions of objects into the training phase. It is an auto-regressive language model, based on the transformer architecture. Base MLLM: [HuggingFaceM4/idefics2-8b](https://huggingface.co/HuggingFaceM4/idefics2-8b) **Paper or resources for more information:** OpenReview: https://openreview.net/forum?id=p3NKpom1VL Arxiv: https://arxiv.org/abs/2501.15140 ## License Idefics2 is licensed under the Apache 2.0 license, and we release the Finedefics checkpoints under the same license. **Where to send questions or comments about the model:** https://github.com/PKU-ICST-MIPL/Finedefics_ICLR2025/issues ## Intended use **Primary intended uses:** The primary use of Finedefics is research on Fine-grained MLLM. **Primary intended users:** The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence. ## Training and evaluation datasets A collection of 6 fine-grained visual recognition datasets, including Stanford Dog-120, Bird-200, FGVC-Aircraft, Flower-102, Oxford-IIIT Pet-37, and Stanford Car-196.