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/d70c8097def32a42ae1ca9570b60e438fe8aae90/training_args.bin
- Command line
-
hf download hf://codechrl/bert-micro-cybersecurity@d70c8097def32a42ae1ca9570b60e438fe8aae90/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/codechrl/bert-micro-cybersecurity/resolve/d70c8097def32a42ae1ca9570b60e438fe8aae90/training_args.bin
5.91 kB
- Xet hash:
- 3533fbb053479f265e92970a798fd0aeb1b04b419813134f67bb7964118bf0fc
- Size of remote file:
- 5.91 kB
- SHA256:
- c7d2976fc6bb4abb6d1b94c1cbdef2c064416e44caca225e76696235e36adfe6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.