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 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/0ffb375dfc1d511d8c8d9e3cd42c809920576b81/model.safetensors
- Command line
-
hf download hf://codechrl/bert-micro-cybersecurity@0ffb375dfc1d511d8c8d9e3cd42c809920576b81/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/codechrl/bert-micro-cybersecurity/resolve/0ffb375dfc1d511d8c8d9e3cd42c809920576b81/model.safetensors
17.7 MB
- Xet hash:
- ad3325b30de5935db4f78054877c9cb718be24144a94edd7ca3c81a9fdd9aec6
- Size of remote file:
- 17.7 MB
- SHA256:
- 26c5935114f21374e4d0f3f42a947134eefbe480e99aafb1d50a514e0acb719a
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