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/f2eee2e722112595cf1cb858e7e58c982da3e327/training_args.bin
- Command line
-
hf download hf://codechrl/bert-micro-cybersecurity@f2eee2e722112595cf1cb858e7e58c982da3e327/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/codechrl/bert-micro-cybersecurity/resolve/f2eee2e722112595cf1cb858e7e58c982da3e327/training_args.bin
5.91 kB
- Xet hash:
- 4510d52654cc81a3127b76938389a63f305ff49353dde0866dcc4b9ee3a35396
- Size of remote file:
- 5.91 kB
- SHA256:
- 270ff26da987430ed62e236e477374bbf8043e69f6a4d442c3695bbabcb8c1cc
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