Instructions to use SzegedAI/bert-tiny5M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SzegedAI/bert-tiny5M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SzegedAI/bert-tiny5M")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SzegedAI/bert-tiny5M") model = AutoModel.from_pretrained("SzegedAI/bert-tiny5M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dd4f17de558e257b9b09a50ad8feb0be40574448145d0d09013e246ef5abe2f0
- Size of remote file:
- 16.8 MB
- SHA256:
- d2e4c784296073c1ac8aec79b84c43596957e6546703f42fef38d6323b11f3d7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.