Instructions to use prajjwal1/bert-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prajjwal1/bert-tiny with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("prajjwal1/bert-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 635 Bytes
7d1bcee | 1 2 3 4 5 6 7 8 9 10 | The following model is a Pytorch pre-trained model obtained from converting Tensorflow checkpoint found in the [official Google BERT repository](https://github.com/google-research/bert). These BERT variants were introduced in the paper [Well-Read Students Learn Better: On the Importance of Pre-training Compact Models](https://arxiv.org/abs/1908.08962). These models are supposed to be trained on a downstream task.
You can check out:
- `prajjwal1/bert-tiny` (L=2, H=128)
- `prajjwal1/bert-mini` (L=4, H=256)
- `prajjwal1/bert-small` (L=4, H=512)
- `prajjwal1/bert-medium` (L=8, H=512)
[@prajjwal_1](https://twitter.com/prajjwal_1)
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