--- license: other license_name: sample-code-license license_link: LICENSE library_name: ml-4m --- # 4M: Massively Multimodal Masked Modeling *A framework for training any-to-any multimodal foundation models.
Scalable. Open-sourced. Across tens of modalities and tasks.* [`Website`](https://4m.epfl.ch) | [`GitHub`](https://github.com/apple/ml-4m) | [`BibTeX`](#citation) Official implementation and pre-trained models for : [**4M: Massively Multimodal Masked Modeling**](https://arxiv.org/abs/2312.06647), NeurIPS 2023 (Spotlight)
*[David Mizrahi](https://dmizrahi.com/)\*, [Roman Bachmann](https://roman-bachmann.github.io/)\*, [Oğuzhan Fatih Kar](https://ofkar.github.io/), [Teresa Yeo](https://aserety.github.io/), [Mingfei Gao](https://fly6464.github.io/), [Afshin Dehghan](https://www.afshindehghan.com/), [Amir Zamir](https://vilab.epfl.ch/zamir/)* **4M-21: An Any-to-Any Vision Model for Tens of Tasks and Modalities**, arXiv 2024
*[Roman Bachmann](https://roman-bachmann.github.io/)\*, [Oğuzhan Fatih Kar](https://ofkar.github.io/)\*, [David Mizrahi](https://dmizrahi.com/)\*, [Ali Garjani](https://garjania.github.io/), [Mingfei Gao](https://fly6464.github.io/), [David Griffiths](https://www.dgriffiths.uk/), [Jiaming Hu](https://scholar.google.com/citations?user=vm3imKsAAAAJ&hl=en), [Afshin Dehghan](https://www.afshindehghan.com/), [Amir Zamir](https://vilab.epfl.ch/zamir/)* 4M is a framework for training "any-to-any" foundation models, using tokenization and masking to scale to many diverse modalities. Models trained using 4M can perform a wide range of vision tasks, transfer well to unseen tasks and modalities, and are flexible and steerable multimodal generative models. We are releasing code and models for "4M: Massively Multimodal Masked Modeling" (here denoted 4M-7), as well as "4M-21: An Any-to-Any Vision Model for Tens of Tasks and Modalities" (here denoted 4M-21). ## Installation For install instructions, please see https://github.com/apple/ml-4m. ## Usage This model can be loaded from Hugging Face Hub as follows: ```python from fourm.models.fm import FM fm = FM.from_pretrained('EPFL-VILAB/4M-21_L') ``` Please see [README_GENERATION.md](https://github.com/apple/ml-4m/blob/main/README_GENERATION.md) for more detailed instructions and https://github.com/apple/ml-4m for other 4M model and tokenizer checkpoints. Safetensors checkpoints are hosted under https://huggingface.co/EPFL-VILAB/4M. ## Citation If you find this repository helpful, please consider citing our work: ``` @inproceedings{4m, title={{4M}: Massively Multimodal Masked Modeling}, author={David Mizrahi and Roman Bachmann and O{\u{g}}uzhan Fatih Kar and Teresa Yeo and Mingfei Gao and Afshin Dehghan and Amir Zamir}, booktitle={Thirty-seventh Conference on Neural Information Processing Systems}, year={2023}, } @article{4m21, title={{4M-21}: An Any-to-Any Vision Model for Tens of Tasks and Modalities}, author={Roman Bachmann and O{\u{g}}uzhan Fatih Kar and David Mizrahi and Ali Garjani and Mingfei Gao and David Griffiths and Jiaming Hu and Afshin Dehghan and Amir Zamir}, journal={arXiv 2024}, year={2024}, } ``` ## License The model weights in this repository are released under the Sample Code license as found in the [LICENSE](LICENSE) file.