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# Use a pipeline as a high-level helper | |
from transformers import pipeline, Conversation | |
import gradio as gr | |
pipe = pipeline("text-classification", model="Junr-syl/sentiments_analysis_DISTILBERT") | |
def my_function(text): | |
out = pipe(text) | |
out = out[0]["label"] # cleaning the output | |
return out | |
with gr.Blocks() as demo : | |
input_componenet = gr.Text("i love AI",label="input") | |
output_componenet = gr.Text(label="output") | |
submit = gr.Button("submit") | |
submit.click(my_function,inputs=[input_componenet],outputs=[output_componenet]) | |
demo.launch() |