FareedKhan-dev/train-llm-from-scratch vs jingyaogong/minimind
Compare FareedKhan-dev/train-llm-from-scratch and jingyaogong/minimind 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
jingyaogong/minimind
An open-source educational project that enables individuals to train and understand a 64M-parameter LLM from scratch in approximately 2 hours using native PyTorch. It covers the complete model training lifecycle and provides open-source data, model architectures, and inference tools.
- License
- Apache-2.0
- Deployment
- Refer to project documentation
- Use cases
- Developers, educators, and researchers who want to inspect and run unabstracted PyTorch code to learn how LLMs are trained from scratch.
- Updated
- —
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