Fill-Mask
Transformers
PyTorch
Safetensors
English
bert
exbert
security
cybersecurity
cyber security
threat hunting
threat intelligence
Instructions to use jackaduma/SecBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jackaduma/SecBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jackaduma/SecBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jackaduma/SecBERT") model = AutoModelForMaskedLM.from_pretrained("jackaduma/SecBERT") - Inference
- Notebooks
- Google Colab
- Kaggle
Kun Ma commited on
Commit ·
e62305c
1
Parent(s): ba83c3b
update README
Browse files
README.md
CHANGED
|
@@ -42,7 +42,9 @@ We proposed to build language model which work on cyber security text, as result
|
|
| 42 |
First, as below shows Fill-Mask pipeline in [Google Bert](), [AllenAI SciBert](https://github.com/allenai/scibert) and our [SecBERT](https://github.com/jackaduma/SecBERT) .
|
| 43 |
|
| 44 |
|
| 45 |
-
<img src="./fill-mask-result.png" width="150%" height="150%">
|
|
|
|
|
|
|
| 46 |
|
| 47 |
---
|
| 48 |
|
|
|
|
| 42 |
First, as below shows Fill-Mask pipeline in [Google Bert](), [AllenAI SciBert](https://github.com/allenai/scibert) and our [SecBERT](https://github.com/jackaduma/SecBERT) .
|
| 43 |
|
| 44 |
|
| 45 |
+
<!-- <img src="./fill-mask-result.png" width="150%" height="150%"> -->
|
| 46 |
+
|
| 47 |
+

|
| 48 |
|
| 49 |
---
|
| 50 |
|