Instructions to use Eraly-ml/KazBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Eraly-ml/KazBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Eraly-ml/KazBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Eraly-ml/KazBERT") model = AutoModelForMaskedLM.from_pretrained("Eraly-ml/KazBERT", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0f6b42ee4238bd30648489d3b011f38f309fd311dd92280b91ee67640bffab1
- Size of remote file:
- 885 MB
- SHA256:
- 49f644a1d1a073c65e2c786583e4c78c1ddf158d911d4cb3971b61d6e3cb8c0c
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