Instructions to use hf-internal-testing/tiny-random-BertForPreTraining with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BertForPreTraining with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BertForPreTraining") model = AutoModelForPreTraining.from_pretrained("hf-internal-testing/tiny-random-BertForPreTraining", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b0ae8c22d24a8fcba39a898b0eaddc3af5c8abfd41fb2ee5a340c6a15e8242b
- Size of remote file:
- 375 kB
- SHA256:
- 61855c68f09190603a069839e37aff07862f9a6f2e313dd8afa60d82fff6f2ef
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.