Welcome spaCy to the Hugging Face Hub

Summary

Hugging Face has integrated spaCy pipelines into the Hugging Face Hub to simplify the distribution, testing, and deployment of natural language processing models across the community. More than 60 canonical models from the spaCy 3.1 release are hosted in the spaCy organization, alongside discoverable community pipelines. Users can package and upload models directly through the command line using the spacy-huggingface-hub extension, which auto-generates required metadata and model cards. Hosted pipelines offer direct pip installation from live wheel URLs, interactive browser exploration, and production-ready HTTP endpoints through the Inference API. The platform provides immediate interactive widget support for named entity recognition components, with upcoming support planned for text classification and part-of-speech tagging pipelines.

Context

spaCy is a widely used library for training and deploying NLP pipelines across tasks like named entity recognition and text classification, but sharing and deploying these packaged pipelines previously required separate hosting workflows.

Approach / What changed

Hugging Face integrated spaCy using the huggingface_hub library, adding a push command to the spaCy CLI via spacy-huggingface-hub, auto-generating model cards and metadata, enabling direct pip installation from wheel URLs, and providing hosted Inference API endpoints with interactive browser widgets.

Takeaways

• The spacy-huggingface-hub extension adds the huggingface-hub push command to the spaCy CLI, enabling package uploads with auto-generated model cards and metadata.
• Models hosted on the Hugging Face Hub can be installed directly using pip via the hosted wheel URL and loaded using standard spacy.load() syntax.
• The hosted Inference API provides interactive browser widgets and HTTP POST endpoints for spaCy named entity recognition components out of the box.

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