Spaces:
Paused
Paused
Update app.py
Browse files
app.py
CHANGED
@@ -1,15 +1,13 @@
|
|
1 |
-
from transformers import AutoModelForQuestionAnswering,
|
2 |
-
AutoTokenizer, pipeline
|
3 |
import gradio as grad
|
4 |
import ast
|
5 |
mdl_name = "deepset/roberta-base-squad2"
|
6 |
-
my_pipeline = pipeline('question-answering', model=mdl_name,
|
7 |
-
|
8 |
def answer_question(question,context):
|
9 |
-
text= "{"+"'question': '"+question+"','context':
|
10 |
-
|
11 |
di=ast.literal_eval(text)
|
12 |
response = my_pipeline(di)
|
13 |
return response
|
14 |
-
grad.Interface(answer_question, inputs=["text","text"],
|
15 |
-
outputs="text").launch()
|
|
|
1 |
+
from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
|
|
|
2 |
import gradio as grad
|
3 |
import ast
|
4 |
mdl_name = "deepset/roberta-base-squad2"
|
5 |
+
my_pipeline = pipeline('question-answering', model=mdl_name, tokenizer=mdl_name)
|
6 |
+
|
7 |
def answer_question(question,context):
|
8 |
+
text= "{"+"'question': '"+question+"','context': '"+context+"'}"
|
9 |
+
|
10 |
di=ast.literal_eval(text)
|
11 |
response = my_pipeline(di)
|
12 |
return response
|
13 |
+
grad.Interface(answer_question, inputs=["text","text"], outputs="text").launch()
|
|