Instructions to use jsun/bert-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jsun/bert-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jsun/bert-tiny")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("jsun/bert-tiny") model = AutoModel.from_pretrained("jsun/bert-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 22a24a0567b63d1d55b31747aaa7b1d2ae0ab07ca250bb8a7bca41517a598faf
- Size of remote file:
- 17.6 MB
- SHA256:
- 3d6b52e393f30e0f2c3555c78c4645b16d6fea7afba98ac679848c468c3e1452
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.