blinkdl/gpt-neox — explained in plain English
Analysis updated 2026-07-18 · repo last pushed 2022-02-25
Train a large language model from scratch across multiple GPUs using YAML configs.
Fine-tune an existing GPT-NeoX model on custom data.
Evaluate a trained model's performance on standard benchmarks.
Download and run inference on the pretrained GPT-NeoX-20B weights.
| blinkdl/gpt-neox | 0xallam/my-recipe | 0xhassaan/nn-from-scratch | |
|---|---|---|---|
| Stars | — | — | 0 |
| Language | Python | Python | Python |
| Last pushed | 2022-02-25 | 2022-11-22 | — |
| Maintenance | Dormant | Dormant | — |
| Setup difficulty | hard | moderate | moderate |
| Complexity | 5/5 | 2/5 | 4/5 |
| Audience | researcher | general | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires multiple high-end GPUs with substantial VRAM and deep familiarity with distributed training concepts.
A research toolkit for training billion-parameter GPT-style language models across many GPUs, built on NVIDIA Megatron and Microsoft DeepSpeed.
Mainly Python. The stack also includes Python, Megatron, DeepSpeed.
Dormant — no commits in 2+ years (last push 2022-02-25).
Setup difficulty is rated hard, with roughly 1day+ to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
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