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01-tokenizers
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02-building-a-tokenizer
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03-data-pipelines
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04-pre-training-mini-gpt
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05-scaling-distributed
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06-instruction-tuning-sft
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07-rlhf
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08-dpo
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09-constitutional-ai-self-improvement
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10-evaluation
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11-quantization
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12-inference-optimization
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13-building-complete-llm-pipeline
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14-open-models-architecture-walkthroughs
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15-speculative-decoding-eagle3
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16-differential-attention-v2
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17-native-sparse-attention
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18-multi-token-prediction
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19-dualpipe-parallelism
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20-deepseek-v3-walkthrough
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21-jamba-hybrid-ssm-transformer
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22-async-hogwild-inference
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25-speculative-decoding
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34-gradient-checkpointing
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README.md
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README.md

Phase 10: LLMs from Scratch

Build, train, and understand large language models.

See ROADMAP.md for the full lesson plan.

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