Instructions to use SzegedAI/bert-small5M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SzegedAI/bert-small5M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SzegedAI/bert-small5M")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SzegedAI/bert-small5M") model = AutoModel.from_pretrained("SzegedAI/bert-small5M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d01c75f02ccc804b81f3e19f56bbd3e14d66f419378e7d1fbcd41464ebebad33
- Size of remote file:
- 112 MB
- SHA256:
- 38ad6727a107835c0672a34740a9b7838b8964157bfe440e881852e78fb9e26e
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