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/7fcce2789d2d8fbe6d29cb73f4d11aa8fb1de8ed/training_args.bin
- Command line
-
hf download hf://codechrl/bert-micro-cybersecurity@7fcce2789d2d8fbe6d29cb73f4d11aa8fb1de8ed/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/codechrl/bert-micro-cybersecurity/resolve/7fcce2789d2d8fbe6d29cb73f4d11aa8fb1de8ed/training_args.bin
5.91 kB
- Xet hash:
- bf5ddca5b18a0eb4994de893095c2b9c3b54ae07240224e1d3618b4748bcf0cf
- Size of remote file:
- 5.91 kB
- SHA256:
- dc671b6041c2b98673dd09895439d3f6a125260f6004a8a89217246ec943146d
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