Instructions to use SzegedAI/bert-base_20M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SzegedAI/bert-base_20M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="SzegedAI/bert-base_20M")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("SzegedAI/bert-base_20M") model = AutoModelForMaskedLM.from_pretrained("SzegedAI/bert-base_20M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- beda82c6049ec1320b77559f7fad14f2c8fa8c72160dbc31d73d4f5700319f54
- Size of remote file:
- 433 MB
- SHA256:
- 54ffc88a43da5cddc9bc180049e319b5d2099df6ef4e36d844827d8e229d1f6f
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