ZeroGPU

Assess

Platforms

A Gradio/Hugging Face deployment option that allocates GPU resources on demand.

Why it's here

Placed in Assess: 3 article(s) of evidence from 1 source(s), led by framework updates, with 0 in the last 30 days. Confidence 43%.

7Hugging Face Blog·8/25/2026framework_update
Gradio adds workflow graphs for AI pipelines
Hugging Face introduced gr.Workflow in Gradio, a graph-based way to build AI pipelines with typed nodes, drag-and-drop execution, and visible intermediate results. The same workflow can be served as a REST API and deployed to Hugging Face Spaces, with nodes able to call models, other Spaces, datasets, or Python functions.
6Hugging Face Blog·4/27/2026open_source
Building scalable web apps with OpenAI Privacy Filter
Hugging Face describes three web apps built around OpenAI's Privacy Filter, an open-source PII detector that can label eight categories of sensitive text in a single 128k-context pass. The examples show document highlighting, image redaction, and shareable redacted text flows implemented with gradio.Server and its queued backend endpoints. The post focuses on how the tool and Gradio can be combined for practical privacy-preserving web experiences.
7Hugging Face Blog·4/1/2026framework_update
Gradio Server enables custom frontends with Gradio backend
Hugging Face introduced gradio.Server, which lets developers build custom web frontends in frameworks like React or plain HTML/JS while still using Gradio’s backend features. It combines FastAPI flexibility with Gradio capabilities such as queuing, concurrency control, SSE streaming, API support, gradio_client compatibility, and ZeroGPU on Spaces.