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LLM Foundations

Model behavior, evals, data quality, synthetic data, agents, inference, and foundation model infrastructure.

Notes on model behavior, evals, data quality, synthetic data, agents, inference, and foundation model infrastructure.

Areas of interest

  • Evaluation methodology and benchmark design
  • Data quality and curation for training and fine-tuning
  • Synthetic data generation and validation
  • Inference optimization and serving infrastructure
  • Model behavior analysis and failure modes

Notes

Notes and writeups coming soon.