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")# 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 tokenizer.json from codechrl/bert-micro-cybersecurity: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/codechrl/bert-micro-cybersecurity/resolve/main/tokenizer.json
- Command line
-
hf download hf://codechrl/bert-micro-cybersecurity/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/codechrl/bert-micro-cybersecurity/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.