You will get cleaned and prepped text data


Project details
You’ll get clean, well-formatted, and model-ready text data delivered in a structured, documented format. Whether you’re working on a classification task, language model fine-tuning, or any other NLP project, I’ll make sure your raw data is prepped for real-world use.
I have a Master’s in Human Language Technology and hands-on experience building NLP pipelines for low-resource languages, including ASR and classification tasks. I work with real-world corpora, so I know how messy text gets, and I know how to clean it without destroying important linguistic cues.
This project includes normalization (case, punctuation, whitespace), filtering unwanted characters, removing empty lines, basic deduplication, and formatting your data into a standard TSV, CSV, or JSONL file for easy downstream use.
I have a Master’s in Human Language Technology and hands-on experience building NLP pipelines for low-resource languages, including ASR and classification tasks. I work with real-world corpora, so I know how messy text gets, and I know how to clean it without destroying important linguistic cues.
This project includes normalization (case, punctuation, whitespace), filtering unwanted characters, removing empty lines, basic deduplication, and formatting your data into a standard TSV, CSV, or JSONL file for easy downstream use.
Data Tool
PythonWhat's included $150
These options are included with the project scope.
$150
- Delivery Time 3 days
- Number of Revisions 1
Optional add-ons
You can add these on the next page.
50,000+ tokens
(+ 1 Day)
+$50
Extra file formats
(+ 1 Day)
+$30
Code delivery
(+ 1 Day)
+$40About Shawna
Technical Writer for Freelance / Contract / Short-term Projects
Gothenburg, Sweden - 7:29 am local time
Steps for completing your project
After purchasing the project, send requirements so Shawna can start the project.
Delivery time starts when Shawna receives requirements from you.
Shawna works on your project following the steps below.
Revisions may occur after the delivery date.
Review Your Data and Requirements
I check your dataset and confirm cleaning needs (e.g., casing, punctuation, encoding, etc.).
Clean and Normalize
I process your text for unwanted characters, line breaks, casing, and formatting issues.