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mkdocs.yml
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# Project information
site_name: Ludwig
site_description: "Declarative machine learning: End-to-end machine learning pipelines using data-driven configurations."
site_author: Piero Molino
site_url: https://ludwig.ai/
# Repository
repo_name: ludwig-ai/ludwig
repo_url: https://github.com/ludwig-ai/ludwig
edit_uri: https://github.com/ludwig-ai/ludwig-docs/edit/master/docs/
# Copyright
copyright: Copyright © 2018 - 2020 Uber Technologies Inc., 2021 - 2022 Linux Foundation Data & AI
# Navigation
nav:
- Ludwig: index.md
- 🚀 Getting Started:
- Getting Started: getting_started/index.md
- Installation: getting_started/installation.md
- Dataset preparation: getting_started/prepare_data.md
- Training: getting_started/train.md
- Prediction and Evaluation: getting_started/evaluate.md
- Hyperopt: getting_started/hyperopt.md
- Serving: getting_started/serve.md
- Distributed training on Ray: getting_started/ray.md
- LLM Fine-tuning: getting_started/llm_finetuning.md
- Ludwig with Docker: getting_started/docker.md
- 📖 User Guide:
- User Guide: user_guide/index.md
- What is Ludwig?: user_guide/what_is_ludwig.md
- How Ludwig Works: user_guide/how_ludwig_works.md
- Command Line Interface: user_guide/command_line_interface.md
- Python API:
- LudwigModel: user_guide/api/LudwigModel.md
- Visualization: user_guide/api/visualization.md
- Datasets:
- Supported Formats: user_guide/datasets/supported_formats.md
- Data Preprocessing: user_guide/datasets/data_preprocessing.md
- Data Postprocessing: user_guide/datasets/data_postprocessing.md
- Dataset Zoo: user_guide/datasets/dataset_zoo.md
- Large Language Models:
- Large Language Models: user_guide/llms/index.md
- Fine-Tuning: user_guide/llms/finetuning.md
- In-Context Learning: user_guide/llms/in_context_learning.md
- Text Classification: user_guide/llms/text_classification.md
- GPUs: user_guide/gpus.md
- Distributed Training:
- Distributed Training: user_guide/distributed_training/index.md
- Fine-Tuning Pretrained Models: user_guide/distributed_training/finetuning.md
- Hyperparameter Optimization: user_guide/hyperopt.md
- Cloud Storage: user_guide/cloud_storage.md
- AutoML: user_guide/automl.md
- Visualizations: user_guide/visualizations.md
- Model Export: user_guide/model_export.md
- Serving: user_guide/serving.md
- Third-Party Integrations: user_guide/integrations.md
- 📚 Configuration:
- Configuration: configuration/index.md
- Model Types: configuration/model_type.md
- Large Language Models: configuration/large_language_model.md
- Preprocessing: configuration/preprocessing.md
- Features:
- Supported Data Types: configuration/features/supported_data_types.md
- Input Features (↑): configuration/features/input_features.md
- Output Features (↓): configuration/features/output_features.md
- ⇅ Binary Features: configuration/features/binary_features.md
- ⇅ Number Features: configuration/features/number_features.md
- ⇅ Category Features: configuration/features/category_features.md
- ⇅ Bag Features: configuration/features/bag_features.md
- ⇅ Set Features: configuration/features/set_features.md
- ⇅ Sequence Features: configuration/features/sequence_features.md
- ⇅ Text Features: configuration/features/text_features.md
- ⇅ Vector Features: configuration/features/vector_features.md
- ↑ Audio Features: configuration/features/audio_features.md
- ↑ Date Features: configuration/features/date_features.md
- ↑ H3 Features: configuration/features/h3_features.md
- ↑ Image Features: configuration/features/image_features.md
- ↑ Time Series Features: configuration/features/time_series_features.md
- Defaults: configuration/defaults.md
- Combiner: configuration/combiner.md
- Trainer: configuration/trainer.md
- Hyperopt: configuration/hyperparameter_optimization.md
- Backend: configuration/backend.md
- 💡 Examples:
- Examples: examples/index.md
- LLMs:
- Fine-tuning for classification: examples/llms/llm_classification.md
- Instruction-tuning llama-2-7b: examples/llms/llm_finetuning.md
- Adapter-based encoder fine-tuning for text classification with deepspeed: examples/llms/llm_finetuning_deepspeed.md
- Adapter-based fine-tuning for text generation: examples/llms/llm_text_generation.md
- Zero-shot batch inference for text generation: examples/llms/llm_zero_shot_text_generation.md
- Zero-shot batch inference for text classification: examples/llms/llm_zero_shot_batch_inference.md
- Few-shot batch inference for text classification (RAG): examples/llms/llm_few_shot_batch_inference.md
- Zero-shot batch inference for tabular classification (TabLLM): examples/llms/llm_tabular_zero_shot_batch_inference.md
- Fine-tuning for tabular classification (TabLLM): examples/llms/llm_tabular_classification.md
- Supervised ML:
- Text Classification: examples/text_classification.md
- Tabular Data Classification: examples/adult_census_income.md
- Image Classification: examples/mnist.md
- Multimodal Classification: examples/multimodal_classification.md
- Hyperparameter Optimization: examples/hyperopt.md
- Fraud with GBMs: examples/gbm_fraud.md
- Sentiment Analysis: examples/sentiment_analysis.md
- Use Cases:
- Named Entity Recognition Tagging: examples/ner_tagging.md
- Natural Language Understanding: examples/nlu.md
- Machine Translation: examples/machine_translation.md
- Chit-Chat Dialogue Modeling through Sequence2Sequence: examples/seq2seq.md
- Sentiment Analysis: examples/sentiment_analysis.md
- One-shot Learning with Siamese Networks: examples/oneshot.md
- Visual Question Answering: examples/visual_qa.md
- Spoken Digit Speech Recognition: examples/speech_recognition.md
- Speaker Verification: examples/speaker_verification.md
- Binary Classification (Titanic): examples/titanic.md
- Timeseries forecasting: examples/forecasting.md
- Timeseries forecasting (Weather): examples/weather.md
- Movie rating prediction: examples/movie_ratings.md
- Multi-label classification: examples/multi_label.md
- Multi-Task Learning: examples/multi_task.md
- Simple Regression - Fuel Efficiency Prediction: examples/fuel_efficiency.md
- Fraud Detection: examples/fraud.md
- 🛠️ Developer Guide:
- Developer Guide: developer_guide/index.md
- How to Contribute: developer_guide/contributing.md
- Codebase Structure: developer_guide/codebase_structure.md
- Ludwig API Guarantees: developer_guide/api_annotations.md
- Add an Encoder: developer_guide/add_an_encoder.md
- Add a Combiner: developer_guide/add_a_combiner.md
- Add a Decoder: developer_guide/add_a_decoder.md
- Add a Feature Type: developer_guide/add_a_feature_type.md
- Add a Metric: developer_guide/add_a_metric.md
- Add a Loss Function: developer_guide/add_a_loss_function.md
- Add a Tokenizer: developer_guide/add_a_tokenizer.md
- Add a Hyperopt Algorithm: developer_guide/add_a_hyperopt.md
- Add a Pretrained Model: developer_guide/add_a_pretrained_model.md
- Add an Integration: developer_guide/add_an_integration.md
- Add a Dataset: developer_guide/add_a_dataset.md
- Style Guidelines and Tests: developer_guide/style_guidelines_and_tests.md
- Unit Test Design Guidelines: developer_guide/unit_test_design_guidelines.md
- Run Tests on GPU Using Ray: developer_guide/run_tests_on_gpu_using_ray.md
- Release Process: developer_guide/release_process.md
- 👋 Community: community.md
- ❓ FAQ: faq.md
# Configuration
site_dir: ../docs/
theme:
name: material
language: en
logo: images/ludwig_logo.svg
favicon: favicon.ico
custom_dir: custom/
palette:
- media: "(prefers-color-scheme: light)" # (1)!
scheme: default
accent: deep orange
primary: grey
toggle:
icon: material/toggle-switch-off-outline
name: Switch to dark mode
- media: "(prefers-color-scheme: dark)" # (2)!
scheme: slate
accent: deep orange
primary: grey
toggle:
icon: material/toggle-switch
name: Switch to light mode
features:
- navigation.indexes
- navigation.tabs.sticky
# Customization
extra_css:
- "stylesheets/extra.css"
- "stylesheets/monokai.css"
- "stylesheets/colorful.css"
# Extensions
markdown_extensions:
- admonition
- toc:
permalink: true
baselevel: 2
- abbr
- attr_list
- pymdownx.snippets
- md_in_html
- pymdownx.details
- pymdownx.emoji
- pymdownx.superfences
- pymdownx.highlight:
extend_pygments_lang:
- name: pycon3
lang: pycon
options:
python3: true
linenums_style: pymdownx-inline
- pymdownx.tabbed:
alternate_style: true
- footnotes
- meta
- tables
- def_list
- attr_list
- pymdownx.emoji:
emoji_index: !!python/name:materialx.emoji.twemoji
emoji_generator: !!python/name:materialx.emoji.to_svg
- pymdownx.superfences:
custom_fences:
- name: mermaid
class: mermaid
format: !!python/name:pymdownx.superfences.fence_code_format
extra:
version:
provider: mike
default: latest
analytics:
provider: google
property: G-H8VVJF9L6G
plugins:
- search
- macros
- mike:
# these fields are all optional; the defaults are as below...
version_selector: true # set to false to leave out the version selector
css_dir: css # the directory to put the version selector's CSS
javascript_dir: js # the directory to put the version selector's JS
canonical_version:
latest # the version for <link rel="canonical">; `null`
# uses the version specified via `mike deploy`