Fill-Mask
Transformers
Safetensors
PyTorch
English
Indonesian
bert
text-classification
token-classification
cybersecurity
named-entity-recognition
tensorflow
masked-language-modeling
Instructions to use codechrl/bert-micro-cybersecurity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codechrl/bert-micro-cybersecurity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="codechrl/bert-micro-cybersecurity")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("codechrl/bert-micro-cybersecurity") model = AutoModelForMaskedLM.from_pretrained("codechrl/bert-micro-cybersecurity", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Training update: 7,754/238,469 rows (3.25%) | +4922 new @ 2025-10-23 04:53:41
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Training update: 6,793/238,453 rows (2.85%) | +100 new @ 2025-10-23 03:04:55
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Training update: 6,788/238,451 rows (2.85%) | +5 new @ 2025-10-23 02:48:14
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Training update: 6,737/238,451 rows (2.83%) | +26 new @ 2025-10-23 02:35:06
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Training update: 1,599/237,655 rows (0.67%) | +1 new @ 2025-10-20 09:42:13
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Model save
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