WHAT IT IS
NeMo is an open-source toolkit from NVIDIA for building, training and customising large models across language, speech and multimodal directions. It works closely with NVIDIA GPUs and acceleration libraries, providing training and inference components. It addresses the difficulty of assembling flows and configurations for large-scale training and fine-tuning on GPU clusters.
Why it matters
It ties the training and customisation flow to NVIDIA’s hardware and software stack, an entry point for that compute on the model-engineering side.
Key specs
- Directions
- Language, speech, multimodal
- Use
- Training, fine-tuning and inference
Related concepts
Training & Inference Infrastructure
Memory decides how large a model you can train, communication how long it takes — raw compute is rarely the bottleneck
Inference Optimization & Serving
Training happens once; inference happens a billion times a day — and serving is torn between fast first tokens and high throughput, which usually pull against each other