This article provides an introduction to Mlflow, an open-source platform for end-to-end machine learning lifecycle management. The article focuses on using MLflow as an orchestrator for machine learning pipelines, explaining the importance of managing complex pipelines in machine learning projects.
This article discusses TinyLlama, an open-source project for a smaller language model with around 1.1B parameters, capable of complex tasks with less memory usage. The article covers implementation, testing, and performance analysis.
Discover how to build custom LLM evaluators for specific real-world needs
Intro to Streamlit
- Simple and complex Streamlit example
- Data and state management in Streamlit apps
- Data widgets for Streamlit apps
- Deploying Streamlit apps
Jemma is a GitHub repository that utilizes AI agents to build software from text-based ideas
It takes an idea in text form and assembles a team to create a web-based prototype
- Works best with Claude models, such as claude-3-haiku-20240307
- Project managers, business owners, and engineers work together to create prototypes
- Users can provide feedback to improve the prototypes
Extract structured data from remote or local LLM models. Predictable output is essential for any serious use of LLMs.
Extract data into Pydantic objects, dataclasses or simple types.
Same API for local file models and remote OpenAI, Mistral AI and other models.
Model management: download models, manage configuration, quickly switch between models.
Tools for evaluating output across local/remote models, for chat-like interaction and more.
No matter how well you craft a prompt begging a model for the output you need, it can always respond something else. Extracting structured data can be a big step into getting predictable behavior from your models.
We introduce LayoutLM, one of the renowned models for extracting information from documents, developed by Microsoft. To tailor a solution for our specific needs, we label our documents using Label Studio, an open-source labeling tool, connected to our remote storage AWS S3.
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