https://github.com/facebookresearch/mmf

A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)
https://github.com/facebookresearch/mmf

captioning deep-learning dialog hateful-memes multi-tasking multimodal pretrained-models pytorch textvqa vqa

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A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)

• Host: GitHub
• URL: https://github.com/facebookresearch/mmf
• Owner: facebookresearch
• License: other
• Created: 2018-06-27T04:52:40.000Z (almost 6 years ago)
• Default Branch: main
• Last Pushed: 2024-03-03T01:46:55.000Z (3 months ago)
• Last Synced: 2024-04-18T04:28:25.033Z (about 1 month ago)
• Topics: captioning, deep-learning, dialog, hateful-memes, multi-tasking, multimodal, pretrained-models, pytorch, textvqa, vqa
• Language: Python
• Homepage: https://mmf.sh/
• Size: 17.1 MB
• Stars: 5,413
• Watchers: 116
• Forks: 921
• Open Issues: 146
• Metadata Files:
  • Readme: README.md
  • Contributing: .github/CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: .github/CODE_OF_CONDUCT.md

Lists

• Awesome-pytorch-list - pythia
• awesome-vision-language-pretraining - [github
• awesome-stars - facebookresearch/mmf - A modular framework for vision & language multimodal research from Facebook AI Research (FAIR) (Python)
• my-awesome-stars - facebookresearch/mmf - A modular framework for vision & language multimodal research from Facebook AI Research (FAIR) (Python)
• awesome-python-machine-learning-resources - GitHub - 30% open · ⏱️ 11.08.2022): (图像数据与CV)
• awesome-list - MMF - A modular framework for vision and language multimodal research by Facebook AI Research, based on PyTorch. (Deep Learning Framework / High-Level DL APIs)

README

        







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---

MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-the-art vision and language models and has powered multiple research projects at Facebook AI Research. See full list of project inside or built on MMF [here](https://mmf.sh/docs/notes/projects).

MMF is powered by PyTorch, allows distributed training and is un-opinionated, scalable and fast. Use MMF to **_bootstrap_** for your next vision and language multimodal research project by following the [installation instructions](https://mmf.sh/docs/). Take a look at list of MMF features [here](https://mmf.sh/docs/getting_started/features).

MMF also acts as **starter codebase** for challenges around vision and

language datasets (The Hateful Memes, TextVQA, TextCaps and VQA challenges). MMF was formerly known as Pythia. The next video shows an overview of how datasets and models work inside MMF. Checkout MMF's [video overview](https://mmf.sh/docs/getting_started/video_overview).

## Installation

Follow installation instructions in the [documentation](https://mmf.sh/docs/).

## Documentation

Learn more about MMF [here](https://mmf.sh/docs).

## Citation

If you use MMF in your work or use any models published in MMF, please cite:

```bibtex

@misc{singh2020mmf,

  author =       {Singh, Amanpreet and Goswami, Vedanuj and Natarajan, Vivek and Jiang, Yu and Chen, Xinlei and Shah, Meet and

                 Rohrbach, Marcus and Batra, Dhruv and Parikh, Devi},

  title =        {MMF: A multimodal framework for vision and language research},

  howpublished = {\url{https://github.com/facebookresearch/mmf}},

  year =         {2020}

}

```

## License

MMF is licensed under BSD license available in [LICENSE](LICENSE) file