uclaml/SPIN

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1254 stars · 106 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Official implementation of Self-Play Fine-Tuning (SPIN), a method that improves language models by having them iteratively generate and discriminate their own training data against human-annotated responses. It includes training scripts, data generation pipelines, and released models/datasets for reproducing the ICML 2024 paper results.

Use cases

• fine-tune an LLM without extra human-annotated data
• reproduce SPIN paper results on Mistral-7B
• improve an SFT model beyond DPO baselines
• generate self-play training data with vLLM
• research iterative self-improvement methods for LLMs

When to choose

• you have an SFT checkpoint and want to boost it without additional annotations
• you're researching self-play or preference-free fine-tuning methods
• you want the reference implementation of the SPIN algorithm

When to avoid

• you need a production training framework with broad model support
• you want actively maintained tooling rather than research code
• you lack GPU resources for 7B-scale fine-tuning

Facets

library · maturity maintenance

llm-training machine-learning deep-learning large-language-models machine-learning deep-learning python self-play fine-tuning llm research-code icml-2024 huggingface gpu linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="uclaml/SPIN")