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 checkpoint-21/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/4cd0124bf6bc0fa7db083c484527a64fd177a27d/checkpoint-21/training_args.bin
- Command line
-
hf download hf://codechrl/bert-micro-cybersecurity@4cd0124bf6bc0fa7db083c484527a64fd177a27d/checkpoint-21/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/codechrl/bert-micro-cybersecurity/resolve/4cd0124bf6bc0fa7db083c484527a64fd177a27d/checkpoint-21/training_args.bin
5.84 kB
- Xet hash:
- 028fcb2fe7746bfe863fcd33a32f0d651c04c877fbad8c227103de7cf8cb39e8
- Size of remote file:
- 5.84 kB
- SHA256:
- 9c3f99d1b2b59eb11e0e6b1b29c895699e0cfe97c3c0f3ec2281a936854293a0
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