Athina home page
Search...
⌘K
Ask AI
AI Hub
Website
Sign-up
Sign-up
Search...
Navigation
Dynamic Columns
Classification
Docs
API / SDK Reference
Guides
FAQs
Documentation
Open-Source Evals
Blog
Email us
Book a call
Getting Started
Introduction
Getting Started
Datasets
Introduction
Creating a dataset
Dynamic Columns
Overview
Run Prompt
API Call
Classification
Extract Entities
Code Execution
Run evaluations (UI)
View Metrics
Run Experiments
Compare datasets
Join Datasets
Export / Download Datasets
SQL Notebook
Automations
Manage Datasets
Delete a Dataset
Evals
Overview
Quick Start
Online Evals
Offline Evals
Preset Evaluators
Custom Evals
Running Evals in UI
Running Evals via SDK
Running Evals in CI/CD
Why Athina Evals?
Cookbooks
Flows
Overview
Concepts
Variables
Sharing Flows
Flow Templates
Blocks
Annotation
Overview
Metrics
Configure Project
View Data
Review Entries
Export Data
Permissions
Prompts
Overview
Concepts
Prompt Syntax
Create Prompt Template
Prompt Versioning
Delete Prompt Slug
List Prompt Slugs
Duplicate Prompt Slug
Run Prompt
Multi-Prompt Playground
Run Evaluations on a Prompt Response
Organize Prompts
Monitoring
Overview
Inference Trace
Analytics
Topic Classification
Export Data from Athina
Continuous Evaluation
Model Performance Metrics
Settings
Custom Models
Sampling Evals
Credits
Integrations
Integrations
Self Hosting
Self-Hosting
Self-Hosting On Azure
Datasets
Import a HuggingFace Dataset
On this page
Inputs
How does it work?
Dynamic Columns
Classification
Classify text into pre-defined labels using an LLM
The
Classification
dynamic column will classify the values from the input columns into user-defined labels.
Output type
:
string
Inputs
Input column
: The column to classify
Labels
: The labels to classify the values into
Language model
: The model to use for classification
Use descriptive labels for the classes for more accurate classification.
How does it work?
Under the hood, we use
Marvin
to do the classification.
API Call
Extract Entities
Assistant
Responses are generated using AI and may contain mistakes.