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 checkpoint-300/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/ba6ca06935cd700689928d269183aff2e5bd5af2/checkpoint-300/training_args.bin
- Command line
-
hf download hf://codechrl/bert-micro-cybersecurity@ba6ca06935cd700689928d269183aff2e5bd5af2/checkpoint-300/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/codechrl/bert-micro-cybersecurity/resolve/ba6ca06935cd700689928d269183aff2e5bd5af2/checkpoint-300/training_args.bin
5.84 kB
- Xet hash:
- a8a6b4b4a28b38d7e6dcf66e94dc28fe12425665c617d122946dbae2f571b5ba
- Size of remote file:
- 5.84 kB
- SHA256:
- 141535d1c3044e612f8853b14d81e1fa4aaa4e2439becfdb8741a6cb1f511a76
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