explosion/spacy-llm
🦙 Integrating LLMs into structured NLP pipelines
This tool helps language professionals quickly set up and test workflows that analyze text. It takes raw text as input and uses large language models (LLMs) to extract information like names, classify sentiment, or summarize content. Data scientists, NLP engineers, or researchers can use this to prototype and build robust text processing applications without needing extensive training data.
1,367 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to rapidly experiment with different text analysis tasks, integrate LLM capabilities into an existing NLP pipeline, or process text using custom prompts without gathering a large dataset.
Not ideal if your primary goal is to deploy highly efficient, low-latency, and cost-optimized NLP models for production at scale, as fine-tuned supervised models are often better for that.
Stars
1,367
Forks
105
Language
Python
License
MIT
Category
Last pushed
Jan 08, 2025
Commits (30d)
0
Dependencies
3
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