Display a Bokeh plot
Search and save datasets generated with a LLM in real time
Filter and view AI model leaderboard data
Create a detailed report from a dataset
Browse and filter AI model evaluation results
Explore tradeoffs between privacy and fairness in machine learning models
Display and analyze PyTorch Image Models leaderboard
Explore and submit NER models
This project is a GUI for the gpustack/gguf-parser-go
Browse LLM benchmark results in various categories
Calculate VRAM requirements for running large language models
Need to analyze data? Let a Llama-3.1 agent do it for you!
Cluster data points using KMeans
Bloom Tokens is a data visualization tool designed to help users create and display Bokeh plots with ease. It serves as a user-friendly interface for generating interactive and web-based visualizations, making data exploration more accessible and engaging.
• Bokeh Plotting: Utilizes the Bokeh library to create interactive visualizations. • Web-Based Interaction: Generates plots that can be easily shared and viewed in web browsers. • Customization Options: Allows users to tailor plot designs to suit their needs. • Ease of Use: Simplifies the process of creating complex visualizations. • Integration Capabilities: Works seamlessly with various data sources and tools.
pip install bloom-tokens.What is Bloom Tokens?
Bloom Tokens is a tool that simplifies the creation of interactive Bokeh visualizations, providing an intuitive interface for data exploration.
How do I get started with Bloom Tokens?
Begin by installing Bloom Tokens using pip, then import it into your project to start creating your visualizations.
Why should I use Bokeh plots?
Bokeh plots offer interactive features and web-based viewing, enhancing data analysis and sharing capabilities.