Instructions to use Erland/bert-base-uncased-jax with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Erland/bert-base-uncased-jax with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Erland/bert-base-uncased-jax")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Erland/bert-base-uncased-jax") model = AutoModel.from_pretrained("Erland/bert-base-uncased-jax") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 144bf586e97cfd57120611c9def705f123524fc61a86a6a250aa1a353eafb0d5
- Size of remote file:
- 438 MB
- SHA256:
- 899d8f1393636def4937c54285d24cdb84fb5f3f948d2a93b64df3e7f273b01e
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