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> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Transformer Math 101

**[EleutherAI](https://daily.dev/sources/eleutherai)** · 11 min read · 0 upvotes · 0 comments

## Summary

A technical reference covering the core mathematics behind training transformer language models. Topics include compute cost estimation using scaling laws (Chinchilla), memory requirements for inference and training (model weights, optimizer states, gradients, activations), and distributed training strategies including ZeRO stages (1/2/3), 3D parallelism (data, tensor, pipeline), and sharded optimizers. Practical engineering heuristics are provided, such as expected TFLOP/s/A100 throughput benchmarks and memory formulas for fitting models on GPU clusters.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://blog.eleuther.ai/transformer-math>

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---

Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#llm](https://daily.dev/tags/llm)

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