Zingg-0.3.3
  • Welcome to Zingg
  • Step By Step Guide
    • Installation
      • Working with Docker Image
    • Hardware Sizing
    • Configuration
    • Creating training data
      • findTrainingData
      • label
      • findAndLabel
      • Using preexisting training data
      • Exporting labeled data as csv
    • Building and saving the model
    • Finding the matches
    • Linking across datasets
  • Data Sources and Sinks
    • Zingg Pipes
    • Snowflake
    • Cassandra
    • MongoDB
    • Neo4j
    • Parquet
  • Running Zingg on Cloud
    • Running on AWS
    • Running on Azure
    • Running on Databricks
  • Zingg Models
    • Pretrained models
  • Improving Accuracy By Defining Own Functions
  • Generating Documentation
  • Output Scores
  • Security And Privacy
  • Updating Labeled Pairs
  • Reporting bugs and contributing
  • Community
  • Frequently Asked Questions
  • Reading Material
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  1. Zingg Models

Pretrained models

PreviousZingg ModelsNextImproving Accuracy By Defining Own Functions

Last updated 2 years ago

Zingg comes with pretrained models for the Febrl dataset under the folder.

models