README.md

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