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FareedKhan-dev/train-llm-from-scratch vs karpathy/autoresearch

Compare FareedKhan-dev/train-llm-from-scratch and karpathy/autoresearch using the current verified snapshot: positioning, license, deployment, use cases, limitations, and original sources.

FareedKhan-dev/train-llm-from-scratch

An end-to-end tutorial project for building, training, and aligning a Large Language Model using plain PyTorch. It guides users through the complete lifecycle from raw text data preparation to text generation, implementing core algorithms without relying on high-level libraries like transformers, trl, or peft.

License
MIT
Deployment
Refer to project documentation
Use cases
Learning & Education
Updated
2026-07-23T17:42:35Z

Original project link

karpathy/autoresearch

An autonomous research loop in which an AI agent edits single-file Python training code, runs short 5-minute experiments on a single NVIDIA GPU, and iteratively keeps or discards changes based on a standardized validation metric.

License
License pending
Deployment
Refer to project documentation
Use cases
AI engineers and researchers running automated, single-file training code iterations on a single NVIDIA GPU. · Users needing an autonomous loop that evaluates changes using a fixed 5-minute time budget and validation bits per byte metric on the same compute platform.
Updated
2026-07-22T00:02:52Z

Original project link

How to choose

First eliminate options that fail required deployment, license, or use-case constraints; then inspect each detail page for limitations and direct evidence.