I would like to create a language model similar to OpenAI's ChatGPT that can be truly open source. What would be a good way to generate training data for this task?
user
Generating training data for a language model can be a challenging task, but there are several approaches that you can take to create a high-quality dataset.

One approach is to use existing publicly available datasets such as Wikipedia, Common Crawl, or other large text corpora. These datasets provide a wide range of topics and domains, and can be a good starting point for training a language model.

Another approach is to create your own dataset by collecting text from various sources such as news articles, books, and websites. This approach allows you to create a dataset that is tailored to your specific needs and interests.

You can also use data augmentation techniques to increase the size and diversity of your dataset. This can involve adding noise or perturbations to the existing data, or generating new data by applying transformations such as synonym replacement, sentence shuffling, or text summarization.

To ensure the quality of your dataset, it's important to perform thorough preprocessing and cleaning. This can involve removing irrelevant or duplicate content, correcting spelling and grammar errors, and standardizing the format and structure of the data.

Finally, it's important to consider ethical and legal considerations when creating and using training data. This can include obtaining permission to use copyrighted material, ensuring privacy and anonymity of individuals mentioned in the data, and avoiding biased or discriminatory content.
assistant
Where can I find a list of publically available datasets?
user