Ludwig
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ludwig-ai/ludwig
Ludwig
ludwig-ai/ludwig
Ludwig
🚀 Getting Started
🚀 Getting Started
Installation
Dataset preparation
Training
Prediction and Evaluation
Hyperopt
Serving
Distributed training on Ray
LLM Fine-tuning
Ludwig with Docker
📖 User Guide
📖 User Guide
What is Ludwig?
How Ludwig Works
Command Line Interface
Python API
Python API
LudwigModel
Visualization
Datasets
Datasets
Supported Formats
Data Preprocessing
Data Postprocessing
Dataset Zoo
Large Language Models
Large Language Models
Fine-Tuning
In-Context Learning
Text Classification
GPUs
Distributed Training
Distributed Training
Fine-Tuning Pretrained Models
Hyperparameter Optimization
Cloud Storage
AutoML
Visualizations
Model Export
Serving
Third-Party Integrations
📚 Configuration
📚 Configuration
Model Types
Large Language Models
Preprocessing
Features
Features
Supported Data Types
Input Features (↑)
Output Features (↓)
⇅ Binary Features
⇅ Number Features
⇅ Category Features
⇅ Bag Features
⇅ Set Features
⇅ Sequence Features
⇅ Text Features
⇅ Vector Features
↑ Audio Features
↑ Date Features
↑ H3 Features
⇅ Image Features
↑ Time Series Features
Defaults
Combiner
Trainer
Hyperopt
Backend
💡 Examples
💡 Examples
LLMs
LLMs
Fine-tuning for classification
Instruction-tuning llama-2-7b
Adapter-based encoder fine-tuning for text classification with deepspeed
Adapter-based fine-tuning for text generation
Zero-shot batch inference for text generation
Zero-shot batch inference for text classification
Few-shot batch inference for text classification (RAG)
Zero-shot batch inference for tabular classification (TabLLM)
Fine-tuning for tabular classification (TabLLM)
Supervised ML
Supervised ML
Text Classification
Tabular Data Classification
Image Classification
Multimodal Classification
Hyperparameter Optimization
Fraud with GBMs
Sentiment Analysis
Use Cases
Use Cases
Named Entity Recognition Tagging
Natural Language Understanding
Machine Translation
Chit-Chat Dialogue Modeling through Sequence2Sequence
Sentiment Analysis
One-shot Learning with Siamese Networks
Visual Question Answering
Spoken Digit Speech Recognition
Speaker Verification
Binary Classification (Titanic)
Timeseries forecasting
Timeseries forecasting (Weather)
Movie rating prediction
Multi-label classification
Multi-Task Learning
Simple Regression - Fuel Efficiency Prediction
Fraud Detection
🛠️ Developer Guide
🛠️ Developer Guide
How to Contribute
Codebase Structure
Ludwig API Guarantees
Add an Encoder
Add a Combiner
Add a Decoder
Add a Feature Type
Add a Metric
Add a Loss Function
Add a Tokenizer
Add a Hyperopt Algorithm
Add a Pretrained Model
Add an Integration
Add a Dataset
Style Guidelines and Tests
Unit Test Design Guidelines
Run Tests on GPU Using Ray
Release Process
👋 Community
❓ FAQ
Includes