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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6262dd959354a8805d1ff302b8e267527cfc08c9beb1adb8c8d0c8b3eff8b4b1
- Size of remote file:
- 5.24 kB
- SHA256:
- 49a71c611b38872245cf1746cb2adc5590d4f3efa157b052d24f39577a822455
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