wehub-resource-sync
e06fe8e8c6
Secret Leaks / trufflehog (push) Failing after 1s
Build documentation / build (push) Failing after 1s
Build documentation / build_other_lang (push) Failing after 0s
CodeQL Security Analysis / CodeQL Analysis (push) Failing after 0s
PR CI / pr-ci (push) Failing after 1s
Slow tests on important models (on Push - A10) / Get all modified files (push) Failing after 1s
Slow tests on important models (on Push - A10) / Model CI (push) Has been skipped
Self-hosted runner (benchmark) / Benchmark (aws-g5-4xlarge-cache) (push) Has been cancelled
New model PR merged notification / Notify new model (push) Has been cancelled
Update Transformers metadata / build_and_package (push) Has been cancelled
53 lines
2.2 KiB
Markdown
53 lines
2.2 KiB
Markdown
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
|
|
|
|
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
|
|
the License. You may obtain a copy of the License at
|
|
|
|
http://www.apache.org/licenses/LICENSE-2.0
|
|
|
|
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
|
|
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
|
|
specific language governing permissions and limitations under the License.
|
|
|
|
⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
|
|
rendered properly in your Markdown viewer.
|
|
|
|
-->
|
|
|
|
# Machine learning apps
|
|
|
|
[Gradio](https://www.gradio.app/), a fast and easy library for building and sharing machine learning apps, is integrated with [`Pipeline`] to quickly create a simple interface for inference.
|
|
|
|
Before you begin, make sure Gradio is installed.
|
|
|
|
```py
|
|
!pip install gradio
|
|
```
|
|
|
|
Create a pipeline for your task, and then pass it to Gradio's [Interface.from_pipeline](https://www.gradio.app/docs/gradio/interface#interface-from_pipeline) function to create the interface. Gradio automatically determines the appropriate input and output components for a [`Pipeline`].
|
|
|
|
Add [launch](https://www.gradio.app/main/docs/gradio/blocks#blocks-launch) to create a web server and start up the app.
|
|
|
|
```py
|
|
from transformers import pipeline
|
|
import gradio as gr
|
|
|
|
pipeline = pipeline("image-classification", model="google/vit-base-patch16-224")
|
|
gr.Interface.from_pipeline(pipeline).launch()
|
|
```
|
|
|
|
The web app runs on a local server by default. To share the app with other users, set `share=True` in [launch](https://www.gradio.app/main/docs/gradio/blocks#blocks-launch) to generate a temporary public link. For a more permanent solution, host the app on Hugging Face [Spaces](https://hf.co/spaces).
|
|
|
|
```py
|
|
gr.Interface.from_pipeline(pipeline).launch(share=True)
|
|
```
|
|
|
|
The Space below is created with the code above and hosted on Spaces.
|
|
|
|
<iframe
|
|
src="https://stevhliu-gradio-pipeline-demo.hf.space"
|
|
frameborder="0"
|
|
width="850"
|
|
height="850"
|
|
></iframe>
|