Instructions to use asifm43/bert-bn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asifm43/bert-bn with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="asifm43/bert-bn")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("asifm43/bert-bn") model = AutoModelForMaskedLM.from_pretrained("asifm43/bert-bn") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f864d7c025c5362bdabd0b58eac65ba38664c4adcb9ea0be69344f594100e294
- Size of remote file:
- 2.86 kB
- SHA256:
- 8efc11aab622c9cfe98c022d658b918372088b4090287e9d1bc6854b7b2c961a
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