Create a large, deduplicated dataset for LLM pre-training
Save user inputs to datasets on Hugging Face
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Create and manage AI datasets for training models
Train a model using custom data
Create and validate structured metadata for datasets
Perform OSINT analysis, fetch URL titles, fine-tune models
Display trending datasets from Hugging Face
ReWrite datasets with a text instruction
Display instructional dataset
Manage and label data for machine learning projects
Convert PDFs to a dataset and upload to Hugging Face
TxT360: Trillion Extracted Text is a powerful tool designed for creating large-scale, deduplicated datasets specifically tailored for pre-training large language models (LLMs). It efficiently processes and extracts text from various sources, ensuring high-quality and diverse data for AI training purposes.
What is TxT360: Trillion Extracted Text used for?
TxT360 is primarily used for creating large-scale, deduplicated datasets for training and fine-tuning large language models. It ensures high-quality, diverse, and relevant text data.
Can I customize the dataset creation process?
Yes, TxT360 allows users to define specific criteria, filter content, and select sources to tailor datasets according to their needs.
How does the deduplication process work?
The deduplication process in TxT360 identifies and removes duplicate or near-duplicate text entries, ensuring that the dataset is unique and efficient for training purposes.
Can TxT360 handle data from multiple sources?
Yes, TxT360 supports data extraction from various sources, including web pages, documents, and other repositories, ensuring a diverse and comprehensive dataset.