Spaces:
Sleeping
Sleeping
added app
Browse files
app.py
ADDED
@@ -0,0 +1,26 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
from transformers import AutoTokenizer, pipeline
|
2 |
+
from optimum.onnxruntime import ORTModelForQuestionAnswering
|
3 |
+
import gradio as gr
|
4 |
+
model = ORTModelForQuestionAnswering.from_pretrained("optimum/roberta-base-squad2")
|
5 |
+
tokenizer = AutoTokenizer.from_pretrained("deepset/roberta-base-squad2")
|
6 |
+
|
7 |
+
onnx_qa = pipeline("question-answering", model=model, tokenizer=tokenizer)
|
8 |
+
|
9 |
+
question = "What's my name?"
|
10 |
+
context = "My name is Philipp and I live in Nuremberg."
|
11 |
+
def get_answer(question):
|
12 |
+
pred = onnx_qa(question, context)
|
13 |
+
return pred
|
14 |
+
|
15 |
+
|
16 |
+
demo = gr.Blocks()
|
17 |
+
|
18 |
+
with demo():
|
19 |
+
with gr.Row():
|
20 |
+
question = gr.Textbox(label='Question', lines= 3)
|
21 |
+
b1 = gr.Button('Get Answer')
|
22 |
+
answer = gr.Textbox(label='Answer', lines=4)
|
23 |
+
b1.click(fn = get_answer, inputs=question, outputs=answer)
|
24 |
+
|
25 |
+
demo.launch()
|
26 |
+
|