fnnx-ai/scikit-llm

Health v2 · maintenance only

Adoption not part of the score

3529 stars · 287 forks observed · 2026-08-28

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

Scikit-LLM is a Python library that integrates large language models like GPT into scikit-learn workflows as estimators. It enables tasks such as zero-shot text classification, summarization, and vectorization using familiar fit/predict APIs.

Use cases

• zero-shot text classification with GPT
• use LLMs inside scikit-learn pipelines
• classify text sentiment without training data
• summarize documents with an LLM estimator
• build ML workflows that mix classical models and LLMs
• label text datasets using large language models

When to choose

• you already use scikit-learn and want LLM-powered estimators
• you need zero-shot classification or text analysis without training a model
• you want to drop LLMs into existing sklearn pipelines

When to avoid

• you need high-throughput, low-latency inference without API costs
• you want to fine-tune or train LLMs yourself
• you don't use Python or the scikit-learn ecosystem

Facets

library · maturity active

machine-learning nlp llm-inference data-science machine-learning large-language-models data-science python scikit-learn llm zero-shot-classification text-analysis openai estimators natural-language-processing

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