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uqlm
Python library for LLM hallucination detection using uncertainty quantification.
FrameworkOpen SourceGrowing
What is uqlm?
uqlm is python library for LLM hallucination detection using uncertainty quantification.
About
UQLM is a Python library designed for detecting hallucinations in Large Language Models (LLMs) through advanced uncertainty quantification techniques. It provides various response-level scorers that quantify the uncertainty of LLM outputs, helping developers assess the reliability of generated content. This tool is particularly useful for researchers and developers working with LLMs who need to ensure the accuracy and trustworthiness of model responses.
Strengths
- Offers multiple scorer types for flexibility in uncertainty quantification.
- Compatible with various LLMs, enhancing usability.
- Provides off-the-shelf solutions for both black-box and white-box scoring.
Limitations
- Some scorer types may incur higher latency and cost due to multiple LLM calls.
- Limited compatibility with LLMs that do not provide token probabilities.
- Advanced users may need to tune ensemble scorers for optimal performance.
Use Cases
Detecting hallucinations in LLM outputs for content generation.Evaluating the reliability of AI-generated responses in chatbots.Improving the accuracy of LLMs in critical applications like healthcare.
Integrations
LangChainChatOpenAIChatVertexAI