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2.3 KiB
2.3 KiB
Aplicații de machine learning
Gradio, o bibliotecă rapidă și ușoară pentru construirea și partajarea de aplicații de machine learning, este integrată cu [Pipeline] pentru a crea rapid o interfață simplă pentru inferență.
Înainte de a începe, asigură-te că Gradio este instalată.
!pip install gradio
Creează un pipeline pentru task-ul tău, iar apoi transmite-l funcției Interface.from_pipeline din Gradio pentru a crea interfața. Gradio determină automat componentele de input și output potrivite pentru un [Pipeline].
Adaugă launch pentru a crea un web server și a porni aplicația.
from transformers import pipeline
import gradio as gr
pipeline = pipeline("image-classification", model="google/vit-base-patch16-224")
gr.Interface.from_pipeline(pipeline).launch()
Aplicația web rulează implicit pe un server local. Pentru a partaja aplicația cu alți utilizatori, setează share=True în launch pentru a genera un link public temporar. Pentru o soluție mai permanentă, găzduiește aplicația pe Hugging Face Spaces.
gr.Interface.from_pipeline(pipeline).launch(share=True)
Space-ul de mai jos este creat cu codul de mai sus și găzduit pe Spaces.