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What is wrong with the CodeGen model that they are using? It is a reasonably large model (up to 16B params) that has already been trained on both natural langu
by jncraton 4y ago
What is wrong with the CodeGen model that they are using?
It is a reasonably large model (up to 16B params) that has already been trained on both natural language and code. I would expect it to underperform larger models, including GPT-3.5 and GPT-4, but this should still be very useful for autocomplete and boilerplate in simpler cases. It is a bit under trained compared to Chinchilla, T5, or LLaMA, but it still performs well.
According to the paper[1], this model is competitive with the largest Codex model that was the basis for Copilot originally.
[1] https://arxiv.org/pdf/2203.13474.pdf https://arxiv.org/pdf/2203.13474.pdf
- MayeulC 4y agoI haven't ran any of these models yet, I had just assumed CodeGen was less performant for "understanding" prompts. You are right that it's probably enough, especially if fine-tuning is an option. Now, I wonder: as the code-base grows, how often, and how, should such tuning take place?