models qna fluency eval

qna-fluency-eval

Overview

Description: The "QnA Fluency Evaluation" is a model to evaluate the Q&A Retrieval Augmented Generation systems by leveraging the state-of-the-art Large Language Models (LLM) to measure the quality and safety of your responses. Utilizing GPT-3.5 as the Language Model to assist with measurements aims to achieve a high agreement with human evaluations compared to traditional mathematical measurements. ### Inference samples Inference type|Python sample (Notebook)|CLI with YAML |--|--|--| Real time|deploy-promptflow-model-python-example|deploy-promptflow-model-cli-example Batch | N/A | N/A ### Sample inputs and outputs (for real-time inference) #### Sample input json { "inputs": { "question": "What feeds all the fixtures in low voltage tracks instead of each light having a line-to-low voltage transformer?", "answer": "The main transformer is the object that feeds all the fixtures in low voltage tracks." } } #### Sample output json { "outputs": { "gpt_fluency": 4 } }

Version: 2

View in Studio: https://ml.azure.com/registries/azureml/models/qna-fluency-eval/version/2

Properties

is-promptflow: True

azureml.promptflow.section: gallery

azureml.promptflow.type: evaluate

azureml.promptflow.name: QnA Fluency Evaluation

azureml.promptflow.description: Compute the Fluency of the answer base on the question using llm.

inference-min-sku-spec: 2|0|14|28

inference-recommended-sku: Standard_DS3_v2