Summarization
Transformers
PyTorch
Safetensors
Enawené-Nawé
bart
text2text-generation
security
shorts
infosec
Instructions to use venkycs/securityShots with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use venkycs/securityShots with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="venkycs/securityShots")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("venkycs/securityShots") model = AutoModelForSeq2SeqLM.from_pretrained("venkycs/securityShots") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Usage
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Staying up-to-date in the CyberSecurity domain is a nightmare, as there are over a thousand security-related updates per day. It is essential for us to focus on relevant content despite the surrounding noise. I have trained a model based on Facebook
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Please contact me at https://www.linkedin.com/in/venkycs/ if you need further details on model or dataset. :
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## Usage
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Staying up-to-date in the CyberSecurity domain is a nightmare, as there are over a thousand security-related updates per day. It is essential for us to focus on relevant content despite the surrounding noise. I have trained a model based on Facebook BART to efficiently summarise security news. The model has been trained on security-related issues and can summarise cyber security news effectively. Use cURL to access this model. The dataset utilised by the model is private, and I may take time to make it accessible to the public.
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Please contact me at https://www.linkedin.com/in/venkycs/ if you need further details on model or dataset. :
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