Alternatives à Attacking Large Language Models
When looking for alternatives to analyzing large language models, consider tools like Lakera AI Security Platform for comprehensive security solutions, or the OWASP Top 10 for Large Language Model Applications to identify specific security risks. For those interested in building their own models, Manning’s resources offer a detailed approach. Evaluating outputs can be done with How to Evaluate Large Language Model Outputs, while exploring the broader impact of LLMs is available through Stanford’s research. These options cater to various needs, from security to development and evaluation.
AI-native security platform for GenAI and enterprise teams.
Lakera AI Security Platform offers a paid service to secure AI and machine learning models, complementing developer needs for model safety a
Tool for identifying security risks in large language model applications.
OWASP Top 10 for Large Language Model Applications offers free guidelines to secure LLMs, complementing Attacking LLMs' approach to identify
Tool for evaluating LLM outputs.
How to Evaluate Large Language Model Outputs offers a freemium model to assess and improve the quality of LLM responses, aiding developers i
Build a Large Language Model with Manning’s resources.
Build a Large Language Model offers a guided approach to creating your own model from scratch, providing developers with customizability and
Towards Data Science provides insights on data science and AI.
Despite Their Feats offers insights and critiques on LLMs, focusing on their limitations for linguists, while Attacking LLMs likely targets