> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo/curator/v26.09/curate-text/tutorials/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/curator/_mcp/server.

# Tutorials

## Docs

- [LLM Judge Runner](https://docs.nvidia.com/nemo/curator/v26.09/curate-text/tutorials/llm-judge.md): Compare jusText and Trafilatura output from Common Crawl records with Curator's LLMJudgeWorkflow and a locally served judge model
- [Recipe](https://docs.nvidia.com/nemo/curator/v26.09/curate-text/tutorials/nemotron-climb.md): Run the end-to-end Nemotron-CLIMB recipe to discover and refine data mixtures for language-model pretraining
- [Stage Reference](https://docs.nvidia.com/nemo/curator/v26.09/curate-text/tutorials/nemotron-climb/stages.md): Commands, inputs, outputs, tuning controls, and restart checks for every stage of the Nemotron-CLIMB recipe


> **Note:** This page contains both a page directory (above) and the landing page content (below). The page directory is generated for agent use and does not appear on the landing page.

> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo/curator/v26.09/curate-text/tutorials/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/curator/_mcp/server.

> Hands-on tutorials for text curation workflows including quality assessment with NeMo Curator

# Text Curation Tutorials

Hands-on tutorials for text curation workflows are available in the [`tutorials/text` directory](https://github.com/NVIDIA-NeMo/Curator/tree/main/tutorials/text) of the NeMo Curator GitHub repository.

## End-to-End Recipes

#### [LLM Judge Runner](/curate-text/tutorials/llm-judge)

Follow this tutorial to prepare Common Crawl records, compare jusText and Trafilatura output, and inspect structured judge scores.

#### [Nemotron-CLIMB Data Curation](/curate-text/tutorials/nemotron-climb)

Discover a pretraining data mixture by embedding, clustering, pruning, tokenizing, training proxy models, and fitting a performance predictor.

## Key Concepts for Tutorial Success

Before diving into the tutorials, familiarize yourself with these essential NeMo Curator concepts:

#### [Pipeline Architecture](/about/concepts/text/data/data-curation-pipeline)

Core processing stages and pipeline concepts for text curation workflows
data-structures
distributed

#### [Quality Assessment](/curate-text/process-data/quality-assessment)

Scoring and filtering techniques used in tutorials
heuristics
classifiers

#### [Data Loading](/curate-text/load-data)

Loading data from various sources
common-crawl
custom-data

#### [Distributed Classification](/curate-text/process-data/quality-assessment/distributed-classifier)

GPU-accelerated classification concepts
gpu
scalable