facebookresearch/lingua

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

4766 stars · 270 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Meta Lingua is a minimal, fast LLM training and inference library built on easy-to-modify PyTorch components for research purposes. It supports end-to-end training, inference, and evaluation of large language models with tools for analyzing speed and stability.

Use cases

• train a 1B parameter LLM from scratch on custom data
• experiment with new transformer architectures and losses
• run LLM inference and evaluation benchmarks
• research LLM training speed and stability
• prepare and shuffle large pretraining datasets from HuggingFace
• launch distributed training jobs on SLURM clusters

When to choose

• you need a hackable, minimal codebase for LLM research
• you want to modify training internals like architectures, losses, or data pipelines
• you need end-to-end training, inference, and evaluation in one lightweight repo
• you work with SLURM-based GPU clusters

When to avoid

• you need a production-ready LLM serving framework
• you want turnkey fine-tuning with high-level APIs like HuggingFace Trainer
• you lack GPU resources or distributed training infrastructure
• you need extensive documentation and long-term stability guarantees

Facets

library · maturity active

llm-training llm-inference machine-learning deep-learning large-language-models deep-learning machine-learning python pytorch llm-research training-framework slurm huggingface meta-ai research gpu linux docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="facebookresearch/lingua")