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gpt2-mini

erwanf

A smaller GPT-2 model with (only) 39M parameters. It was pretrained on a subset of OpenWebText, the open-source version of the pretraining dataset used by OpenAI for the original GPT-2 models. The purpose of this model is mainly for research and education. Its small size allows for fast experiments in resource-limited settings, while still being able of generating complex and coherent text. The architecture relies on the GPT-2 model, with smaller dimensions and less layers. It uses the same tokenizer as GPT-2. We used the first 2M rows from the OpenWebText dataset, out of which we use 1k for test and validation sets.

Text generation

Input Text→ Output Text

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Adjust monthly token usage to compare estimated API costs.

Monthly input tokens 10 MMonthly output tokens 2 M1 M = 1 million tokens · USD
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Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.

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gpt2-mini

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