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 model.safetensors from codechrl/bert-micro-cybersecurity: direct link, hf CLI and curl.
- Browser
- Download file 17.7 MB
-
https://huggingface.co/codechrl/bert-micro-cybersecurity/resolve/main/model.safetensors
- Command line
-
hf download hf://codechrl/bert-micro-cybersecurity/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/codechrl/bert-micro-cybersecurity/resolve/main/model.safetensors
17.7 MB
- Xet hash:
- 0cdd9e89cbecfe7485f2ff8608232fe5d8ef32228fd5e64a9c5ec43886bb4a6c
- Size of remote file:
- 17.7 MB
- SHA256:
- 12917da4dfc3f5c4ad90d2fe93c0cdd57e1e4c1df7f3d01b8c94b8952db28272
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