Fill-Mask
Transformers
PyTorch
Safetensors
English
bert
Cybersecurity
Cyber Security
Information Security
Computer Science
Cyber Threats
Vulnerabilities
Vulnerability
Malware
Attacks
Instructions to use markusbayer/CySecBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use markusbayer/CySecBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="markusbayer/CySecBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("markusbayer/CySecBERT") model = AutoModelForMaskedLM.from_pretrained("markusbayer/CySecBERT") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit ·
e4ed737
1
Parent(s): d252cd0
Adding `safetensors` variant of this model
Browse filesThis is an automated PR create with https://huggingface.co/spaces/safetensors/convert
This new file is equivalent to `pytorch_model.bin` but safe in the sense that
no arbitrary code can be put into it.
These files also happen to load much faster than their pytorch counterpart:
https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb
The widgets on your model page will run using this model even if this is not merged
making sure the file actually works.
Feel free to ignore this PR.
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:14bb036035514c9376ff75b7e4e53b4b02b63bf62d4c3b9a8bfd347296fbacef
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size 438085080
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