Learn to create diverse test cases using both intrinsic and extrinsic metrics and balance the performance with resource management for reliable LLMs.
The best LLMs are already familiar with chess logic and concepts; we must simply guide the model to output the board (a novel format, and here, our model “customization”) according to the logic it’s already familiar with. We put this scenario to the...
A prompt to an LLM (ChatGPT 3.5 turbo) that takes in the facts in the test bank and writes a question customized to a student’s request based on the provided facts A Python CLI that takes in the user’s question and sends requests to OpenAI’s ChatGPT model To complete this tutorial...
If you are running another service on localhost like Chroma, LocalAi, or LMStudio you will need to usehttp://host.docker.internal:xxxxto access the service from within the docker container using AnythingLLM aslocalhost:xxxxwill not resolve for the host system. ...
and Relevance to a given question or context. Prompts for model assessment LLMs are highly flexible, and they can be quickly changed to improve performance with Chain-of-Thought or few-shot approaches customized to a specific use case. Research indicates that these methods are more performant ...
In 2025, chatbot functionality improved even more thanks to smart LLM and ML algorithms alongside the rise of AI assistants. In fact,89%of recruiters who improve their processes with AI use it frequently or very frequently. Another case of how the recruitment industry wins from technologies isTal...
If you're new to using AI as a manager, here’s a quick exercise to get you started. Open up a LLM, such as ChatGPT, and test out the prompts below. Many LLMs are free to use, you simply need to set up an account. The following are prompts that can help managers in separate...
The learning mechanism of an AI model is based on a trial-and-error method. AI models deliver multiple solutions to a particular problem and thereby retain the most successful ones in their database to use in the future. Another method they use is the rote memorizing method. ...
This sample shows how to create two AKS-hosted chat applications that use OpenAI, LangChain, ChromaDB, and Chainlit using Python and deploy them to an AKS environment built in Terraform. - Azure-Samples/aks-openai-chainlit-terraform
such as k-fold cross-validation on the training set to find the “optimal” set of hyperparameters for your model. If you are done with hyperparameter tuning, use the independent test set to get an unbiased estimate of its performance. Below I inserted a figure to illustrate the difference...