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") - Notebooks
- Google Colab
- Kaggle
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## <span style="color:#4CAF50;"> Model Overview</span>
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**KazBERT** is a BERT-based model fine-tuned specifically for Kazakh using Masked Language Modeling (MLM). It is based on `bert-base-uncased` and uses a custom tokenizer trained on Kazakh text.
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**If you find KazBERT useful please press like button**
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## <span style="color:#4CAF50;"> Model Overview</span>
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**KazBERT** is a BERT-based model fine-tuned specifically for Kazakh using Masked Language Modeling (MLM). It is based on `bert-base-uncased` and uses a custom tokenizer trained on Kazakh text.
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