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
Download training_args.bin from codechrl/bert-micro-cybersecurity: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/codechrl/bert-micro-cybersecurity/resolve/5801bcc1bfa77b5fcb0d577793683f98ef60e749/training_args.bin
- Command line
-
hf download hf://codechrl/bert-micro-cybersecurity@5801bcc1bfa77b5fcb0d577793683f98ef60e749/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/codechrl/bert-micro-cybersecurity/resolve/5801bcc1bfa77b5fcb0d577793683f98ef60e749/training_args.bin
5.84 kB
- Xet hash:
- ed87c812cea0f42cdeea1db66e47d65fbdd352fdbe48e2f2b98fd300cb157ce3
- Size of remote file:
- 5.84 kB
- SHA256:
- 469013be13b827810f1ecf5adb60b642c5ff42e7dbdfa2d95720099142d4a56e
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