#gpt-2

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fromHackernoon
1 year ago

Empirical Results: GPT-2 Analysis of Transformer Memorization & Loss | HackerNoon

These experiments with GPT-2 medium on OpenWebText validate the radius hypothesis from our theoretical framework, measuring activation distances in the last layer for next-token prediction.
Roam Research
Artificial intelligence
fromHackernoon
1 year ago

GPT-2 Study Shows How Language Models Can Amplify Political Bias | HackerNoon

The study emphasizes the importance of addressing bias amplification in large language models, particularly in the context of political bias in media.
fromHackernoon
8 months ago

How Tokenizer Choices Shape Hidden Risks in Popular Language Models | HackerNoon

Tokenization methods can reveal under-trained tokens that impact model performance.
Identifying and addressing under-trained tokens is crucial for improving language model accuracy.
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