Update app.py
Browse files
app.py
CHANGED
@@ -1,13 +1,36 @@
|
|
1 |
import streamlit as st
|
2 |
import torch
|
3 |
-
import
|
|
|
4 |
|
5 |
st.markdown("### Articles classificator.")
|
6 |
# st.markdown("<img width=200px src='https://rozetked.me/images/uploads/dwoilp3BVjlE.jpg'>", unsafe_allow_html=True)
|
7 |
|
8 |
@st.cache
|
9 |
def LoadModel():
|
10 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
11 |
|
12 |
model, tokenizer = LoadModel()
|
13 |
|
|
|
1 |
import streamlit as st
|
2 |
import torch
|
3 |
+
from transformers import AutoTokenizer, AutoModel, pipeline
|
4 |
+
from torch import nn
|
5 |
|
6 |
st.markdown("### Articles classificator.")
|
7 |
# st.markdown("<img width=200px src='https://rozetked.me/images/uploads/dwoilp3BVjlE.jpg'>", unsafe_allow_html=True)
|
8 |
|
9 |
@st.cache
|
10 |
def LoadModel():
|
11 |
+
model_name = 'bert-base-uncased'
|
12 |
+
tokenizer = AutoTokenizer.from_pretrained(model_name)
|
13 |
+
bert = AutoModel.from_pretrained(model_name)
|
14 |
+
|
15 |
+
class devops_model(nn.Module):
|
16 |
+
def __init__(self):
|
17 |
+
super(devops_model, self).__init__()
|
18 |
+
self.bert = bert
|
19 |
+
self.fc = nn.Sequential(
|
20 |
+
nn.Linear(768, 768),
|
21 |
+
nn.ReLU(),
|
22 |
+
nn.Dropout(0.3),
|
23 |
+
nn.BatchNorm1d(768),
|
24 |
+
nn.Linear(768, 5),
|
25 |
+
nn.LogSoftmax(dim=-1)
|
26 |
+
)
|
27 |
+
|
28 |
+
def forward(self, train_batch):
|
29 |
+
emb = self.bert(**train_batch)['pooler_output']
|
30 |
+
return self.fc(emb)
|
31 |
+
|
32 |
+
return torch.load('model.pt'), tokenizer
|
33 |
+
|
34 |
|
35 |
model, tokenizer = LoadModel()
|
36 |
|