Spaces:
Sleeping
Sleeping
Create app.py
Browse files
app.py
ADDED
@@ -0,0 +1,28 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import gradio as gr
|
2 |
+
import onnxruntime
|
3 |
+
from transformers import AutoTokenizer
|
4 |
+
import torch, json
|
5 |
+
|
6 |
+
token = AutoTokenizer.from_pretrained('pablocosta/bertabaporu-large-uncased')
|
7 |
+
|
8 |
+
with open("genre_types_encoded.json", "r") as fp:
|
9 |
+
types = json.load(fp)
|
10 |
+
|
11 |
+
types = list(types)
|
12 |
+
|
13 |
+
|
14 |
+
inf_session = onnxruntime.InferenceSession('https://drive.google.com/file/d/1-8Iru2d_NjNmZ_czxu87IjIX1meBea4E/view?usp=sharing')
|
15 |
+
input_name = inf_session.get_inputs()[0].name
|
16 |
+
output_name = inf_session.get_outputs()[0].name
|
17 |
+
|
18 |
+
def classify(review):
|
19 |
+
input_ids = token(review)['input_ids'][:512]
|
20 |
+
logits = inf_session.run([output_name], {input_name: [input_ids]})[0]
|
21 |
+
logits = torch.FloatTensor(logits)
|
22 |
+
probs = torch.sigmoid(logits)[0]
|
23 |
+
return dict(zip(types, map(float, probs)))
|
24 |
+
|
25 |
+
|
26 |
+
label = gr.outputs.Label(num_top_classes=5)
|
27 |
+
iface = gr.Interface(fn=classify, inputs="text", outputs=label)
|
28 |
+
iface.launch(inline=False)
|