TīmeklisThe language modeling task is to assign a probability for the likelihood of a given word (or a sequence of words) to follow a sequence of words. A sequence of tokens are passed to the embedding layer first, followed by a positional encoding layer to account for the order of the word (see the next paragraph for more details). Tīmeklis2024. gada 14. jūl. · We find that existing language modeling datasets contain many near-duplicate examples and long repetitive substrings. As a result, over 1% of the unprompted output of language models trained on these datasets is copied verbatim from the training data. We develop two tools that allow us to deduplicate training …
The Pile - Eleuther
Tīmeklis2024. gada 23. maijs · Language models (LMs) have been shown to memorize a great deal of factual knowledge contained in their training data. But when an LM … Tīmeklis2024. gada 10. apr. · Understanding how the model works, in a very simplified form, let's discuss the mathematical impact of removing data on a large language model. … nba news and trade rumors lakers
Improving language model behavior by training on a curated dataset - OpenAI
Tīmeklis2024. gada 14. dec. · It has become common to publish large (billion parameter) language models that have been trained on private datasets. This paper demonstrates that in such settings, an adversary can perform a training data extraction attack to recover individual training examples by querying the language model. Tīmeklis2024. gada 2. jūn. · Best practices include comprehensive model evaluation to properly assess limitations, minimizing potential sources of bias in training corpora, and … Tīmeklis2024. gada 7. apr. · Bibkey: moore-lewis-2010-intelligent. Cite (ACL): Robert C. Moore and William Lewis. 2010. Intelligent Selection of Language Model Training Data. In Proceedings of the ACL 2010 Conference Short Papers, pages 220–224, Uppsala, Sweden. Association for Computational Linguistics. Cite (Informal): nba news anthony edwards