Instructions to use hf-tiny-model-private/tiny-random-MobileBertForNextSentencePrediction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MobileBertForNextSentencePrediction with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForNextSentencePrediction tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MobileBertForNextSentencePrediction") model = AutoModelForNextSentencePrediction.from_pretrained("hf-tiny-model-private/tiny-random-MobileBertForNextSentencePrediction") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49f08c9e823ca61d74273380838eed0987960d023143e28577a44c6e863f766b
- Size of remote file:
- 2.87 MB
- SHA256:
- d2b1c6a8ac39a653e63b621f3367d3992b8836fca1efa90c49d76585cced348c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.