InstructLab Fine-Tuning Guide: Updates and Insights for the Musician Example

The blog post outlines updates on fine-tuning a model with the InstructLab , detailing tasks like data preparation, validation, synthetic data generation, model training, and testing. It emphasizes the need for extensive and accurate input for effective training, while only minimal changes in the overall process since previous versions, particularly in handling data quality. This blog post contains updates related to my blog post InstructLab and Taxonomy tree: LLM Foundation Model Fine-tuning Guide | Musician Example.

February 4, 2025 2

Bee Agent example for a simple travel assistant using a custom tool and observe the agent behavior in detail (Bee Framework 0.0.34 and watsonx.ai)

This blog post explains the implementation of a custom travel assistant agent using the Bee Agent Framework. It covers creating a tool to suggest vacation locations and utilizing weather data, integrating with MLFlow for observability. The article emphasizes practical execution steps, system requirements, and the motivation behind combining location and weather insights for user queries.

November 22, 2024 5

Unlock watsonx Capabilities: Where do you start finding implementation examples when you are an AI engineer or developer?

IBM has launched the watsonx Developer Hub, consisting of four sections: Get Started, Capabilities, Guides, and Support. This Hub is a valuable resource for developers looking to learn about watsonx, emphasizing its significance in the development process.

October 24, 2024 0

An Example of how use the “Bee Agent Framework” (v0.0.33) with watsonx.ai

This blog post explores the Bee Agent Framework integration with watsonx.ai, detailing the setup process for a weather agent example on MacOS. It discusses necessary installations, environment variable configurations, and code updates needed due to framework changes. The execution output illustrates how the agent retrieves current weather data for Las Vegas.

October 23, 2024 3

Land of Confusion using Classifications, and Metrics for a nonspecific Ground Truth

This blog post examines the Confusion Matrix as a metric for evaluating the performance of large language models (LLMs) in classification tasks, especially legal document analysis. It discusses the calculation of key classification metrics like Accuracy, Precision, Recall, and F1 score, emphasizing the challenges of using a broadly defined Ground Truth.

October 8, 2024 2

Enhance the LangChain AI Agent Weather Query Example with a Dependency Graph Visualization

This blog post demonstrates how to simply add a dependency graph to a runnable chain for a LangChain AI Agent example with WatsonxLLM for a Weather Queries application.

August 26, 2024 0

Implementing LangChain AI Agent with WatsonxLLM for a Weather Queries application

This blog post describes the customization of the LangChain AI Agent example from IBM Developer using Watsonx in Python. It demonstrates the implementation of a weather query application with detailed steps. The post offers insight into model parameters, creating prompts, agent chains, tool definitions, and execution. Additionally, it provides links to additional resources for further exploration.

August 20, 2024 7

Integrating langchain_ibm with watsonx and LangChain for function calls: Example and Tutorial

The blog post demonstrates using the ChatWatsonx class of langchain_ibm for "function calls" with LangChain and IBM watsonx™ AI. It provides an example of a chat function call for weather information for various cities. The post also includes instructions to set up and run the example. Additional resources and examples are also provided.

August 12, 2024 2

InstructLab and Taxonomy tree: LLM Foundation Model Fine-tuning Guide | Musician Example

The blog post introduces InstructLab, a project by IBM and Red Hat, outlining the fine-tuning process of the model "MODELS/MERLINITE-7B-LAB-Q4_K_M.GGUF." This involves data preparation, model training, testing, and conversion, finally serving the model to verify its accuracy, by using a personal musician example.

June 21, 2024 6

Fine-tune LLM foundation models with the InstructLab an Open-Source project introduced by IBM and Red Hat

This blog post provides a step-by-step guide to setting up InstructLab CLI on an Apple Laptop with an Apple M3 chip, including an overview of InstructLab and its benefits. It also mentions supported models and detailed setup instructions. Additionally, it refers to a Red Hat YouTube demonstration and highlights the project's potential impact.

June 20, 2024 4

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