Spaces:
Running
on
Zero
Running
on
Zero
import gradio | |
import json | |
from transformers import pipeline | |
from transformers import AutoTokenizer | |
from fastapi.middleware.cors import CORSMiddleware | |
classifier = pipeline(task='zero-shot-classification', model='tasksource/deberta-small-long-nli', device=0) | |
app.add_middleware( | |
CORSMiddleware, | |
allow_origins=["https://statosphere-3704059fdd7e.c5v4v4jx6pq5.win"], | |
allow_credentials=False, | |
allow_methods=["*"], | |
allow_headers=["*"], | |
) | |
def zero_shot_classification(data_string): | |
print(data_string) | |
data = json.loads(data_string) | |
print(data) | |
results = classifier(data['sequence'], candidate_labels=data['candidate_labels'], hypothesis_template=data['hypothesis_template'], multi_label=data['multi_label']) | |
response_string = json.dumps(results) | |
return response_string | |
gradio_interface = gradio.Interface( | |
fn = zero_shot_classification, | |
inputs = gradio.Textbox(label="JSON Input"), | |
outputs = gradio.Textbox() | |
) | |
gradio_interface.launch() |