Instructions to use microsoft/amos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/amos with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("microsoft/amos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: mit | |
| # Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators | |
| This model card contains the AMOS model (**base++** version) proposed in [this paper](). The official GitHub repository can be found [here](https://github.com/microsoft/AMOS). | |
| # Citation | |
| If you find this model card useful for your research, please cite the following paper: | |
| ``` | |
| @inproceedings{meng2022amos, | |
| title={Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators}, | |
| author={Meng, Yu and Xiong, Chenyan and Bajaj, Payal and Tiwary, Saurabh and Bennett, Paul and Han, Jiawei and Song, Xia}, | |
| booktitle={ICLR}, | |
| year={2022} | |
| } | |
| ``` |