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/03eb0c616df33a8bcf3f32293d6fd22f7bb4e91b/training_args.bin
- Command line
-
hf download hf://codechrl/bert-micro-cybersecurity@03eb0c616df33a8bcf3f32293d6fd22f7bb4e91b/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/codechrl/bert-micro-cybersecurity/resolve/03eb0c616df33a8bcf3f32293d6fd22f7bb4e91b/training_args.bin
5.91 kB
- Xet hash:
- 072cd5bf81a58fa9023c6f059b91fa4453698c419ee88d50cac5cc1491f6effe
- Size of remote file:
- 5.91 kB
- SHA256:
- 5cce5a9abe8c5c839098ffd9ae4de39cdab0c52a8cabb0d1c6c17c86f920e8a0
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