Replit AI Podcast 02: Unleashing LLMs in Production: Challenges and Opportunities with Chip Huyen
8 snips
May 24, 2023 AI Snips
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Replit's YOLO Run
- Replit's 2.7B parameter model was trained in three days on 256 GPUs after a slow ramp-up.
- Initial smaller test runs with a 300M parameter model lacked confidence, leading to a final "yolo" run.
Fine-tuning and Bespoke LLMs
- Replit fine-tuned their model with their own data after the initial training.
- Few companies train bespoke LLMs from scratch, making Replit's approach noteworthy.
Continual Learning for LLMs
- Continual learning for LLMs is crucial due to the rapid staleness of models.
- Chip Huyen emphasizes that incorporating context into models is superior to prompt engineering workarounds.