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 5.91 kB
-
https://huggingface.co/codechrl/bert-micro-cybersecurity/resolve/3fa0de5324d229d722ebc94f557cbaea63bbd4e7/training_args.bin
- Command line
-
hf download hf://codechrl/bert-micro-cybersecurity@3fa0de5324d229d722ebc94f557cbaea63bbd4e7/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/codechrl/bert-micro-cybersecurity/resolve/3fa0de5324d229d722ebc94f557cbaea63bbd4e7/training_args.bin
5.91 kB
- Xet hash:
- 6fa6ad70bdb563b8d3e23b77b17e75699147a0d2c8d464ae63c14c54031237a9
- Size of remote file:
- 5.91 kB
- SHA256:
- 19eb1835ee612ca9c4b19284295fbdb3b2dccc47598cc71ef4fcc9a9bd588ad0
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