Commit
·
2c043d7
1
Parent(s):
d8b47e1
Upload 2 files
Browse files- evaluation_comp.ipynb +1649 -0
- sontotalmodel_finallll.pt +3 -0
evaluation_comp.ipynb
ADDED
|
@@ -0,0 +1,1649 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"cells": [
|
| 3 |
+
{
|
| 4 |
+
"cell_type": "code",
|
| 5 |
+
"execution_count": 1,
|
| 6 |
+
"metadata": {
|
| 7 |
+
"colab": {
|
| 8 |
+
"base_uri": "https://localhost:8080/"
|
| 9 |
+
},
|
| 10 |
+
"id": "GzE_W3UhwV2_",
|
| 11 |
+
"outputId": "add0f0f9-1722-40c0-e251-40768042e98d"
|
| 12 |
+
},
|
| 13 |
+
"outputs": [
|
| 14 |
+
{
|
| 15 |
+
"name": "stdout",
|
| 16 |
+
"output_type": "stream",
|
| 17 |
+
"text": [
|
| 18 |
+
"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
|
| 19 |
+
"Collecting gradio\n",
|
| 20 |
+
" Downloading gradio-3.24.1-py3-none-any.whl (15.7 MB)\n",
|
| 21 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m15.7/15.7 MB\u001b[0m \u001b[31m34.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 22 |
+
"\u001b[?25hRequirement already satisfied: markdown-it-py[linkify]>=2.0.0 in /usr/local/lib/python3.9/dist-packages (from gradio) (2.2.0)\n",
|
| 23 |
+
"Collecting ffmpy\n",
|
| 24 |
+
" Downloading ffmpy-0.3.0.tar.gz (4.8 kB)\n",
|
| 25 |
+
" Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
|
| 26 |
+
"Collecting python-multipart\n",
|
| 27 |
+
" Downloading python_multipart-0.0.6-py3-none-any.whl (45 kB)\n",
|
| 28 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m45.7/45.7 KB\u001b[0m \u001b[31m3.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 29 |
+
"\u001b[?25hRequirement already satisfied: pydantic in /usr/local/lib/python3.9/dist-packages (from gradio) (1.10.7)\n",
|
| 30 |
+
"Collecting semantic-version\n",
|
| 31 |
+
" Downloading semantic_version-2.10.0-py2.py3-none-any.whl (15 kB)\n",
|
| 32 |
+
"Collecting websockets>=10.0\n",
|
| 33 |
+
" Downloading websockets-11.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (129 kB)\n",
|
| 34 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m129.5/129.5 KB\u001b[0m \u001b[31m6.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 35 |
+
"\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.9/dist-packages (from gradio) (1.22.4)\n",
|
| 36 |
+
"Requirement already satisfied: pandas in /usr/local/lib/python3.9/dist-packages (from gradio) (1.4.4)\n",
|
| 37 |
+
"Requirement already satisfied: requests in /usr/local/lib/python3.9/dist-packages (from gradio) (2.27.1)\n",
|
| 38 |
+
"Requirement already satisfied: jinja2 in /usr/local/lib/python3.9/dist-packages (from gradio) (3.1.2)\n",
|
| 39 |
+
"Collecting uvicorn\n",
|
| 40 |
+
" Downloading uvicorn-0.21.1-py3-none-any.whl (57 kB)\n",
|
| 41 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m57.8/57.8 KB\u001b[0m \u001b[31m2.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 42 |
+
"\u001b[?25hRequirement already satisfied: pillow in /usr/local/lib/python3.9/dist-packages (from gradio) (8.4.0)\n",
|
| 43 |
+
"Collecting aiofiles\n",
|
| 44 |
+
" Downloading aiofiles-23.1.0-py3-none-any.whl (14 kB)\n",
|
| 45 |
+
"Collecting aiohttp\n",
|
| 46 |
+
" Downloading aiohttp-3.8.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.0 MB)\n",
|
| 47 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.0/1.0 MB\u001b[0m \u001b[31m8.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 48 |
+
"\u001b[?25hRequirement already satisfied: altair>=4.2.0 in /usr/local/lib/python3.9/dist-packages (from gradio) (4.2.2)\n",
|
| 49 |
+
"Requirement already satisfied: matplotlib in /usr/local/lib/python3.9/dist-packages (from gradio) (3.7.1)\n",
|
| 50 |
+
"Collecting gradio-client>=0.0.5\n",
|
| 51 |
+
" Downloading gradio_client-0.0.7-py3-none-any.whl (14 kB)\n",
|
| 52 |
+
"Collecting fastapi\n",
|
| 53 |
+
" Downloading fastapi-0.95.0-py3-none-any.whl (57 kB)\n",
|
| 54 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m57.1/57.1 KB\u001b[0m \u001b[31m8.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 55 |
+
"\u001b[?25hCollecting httpx\n",
|
| 56 |
+
" Downloading httpx-0.23.3-py3-none-any.whl (71 kB)\n",
|
| 57 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m71.5/71.5 KB\u001b[0m \u001b[31m9.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 58 |
+
"\u001b[?25hCollecting huggingface-hub>=0.13.0\n",
|
| 59 |
+
" Downloading huggingface_hub-0.13.3-py3-none-any.whl (199 kB)\n",
|
| 60 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m199.8/199.8 KB\u001b[0m \u001b[31m23.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 61 |
+
"\u001b[?25hCollecting mdit-py-plugins<=0.3.3\n",
|
| 62 |
+
" Downloading mdit_py_plugins-0.3.3-py3-none-any.whl (50 kB)\n",
|
| 63 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m50.5/50.5 KB\u001b[0m \u001b[31m6.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 64 |
+
"\u001b[?25hRequirement already satisfied: markupsafe in /usr/local/lib/python3.9/dist-packages (from gradio) (2.1.2)\n",
|
| 65 |
+
"Requirement already satisfied: typing-extensions in /usr/local/lib/python3.9/dist-packages (from gradio) (4.5.0)\n",
|
| 66 |
+
"Collecting orjson\n",
|
| 67 |
+
" Downloading orjson-3.8.9-cp39-cp39-manylinux_2_28_x86_64.whl (144 kB)\n",
|
| 68 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m144.1/144.1 KB\u001b[0m \u001b[31m18.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 69 |
+
"\u001b[?25hRequirement already satisfied: pyyaml in /usr/local/lib/python3.9/dist-packages (from gradio) (6.0)\n",
|
| 70 |
+
"Collecting pydub\n",
|
| 71 |
+
" Downloading pydub-0.25.1-py2.py3-none-any.whl (32 kB)\n",
|
| 72 |
+
"Requirement already satisfied: jsonschema>=3.0 in /usr/local/lib/python3.9/dist-packages (from altair>=4.2.0->gradio) (4.3.3)\n",
|
| 73 |
+
"Requirement already satisfied: toolz in /usr/local/lib/python3.9/dist-packages (from altair>=4.2.0->gradio) (0.12.0)\n",
|
| 74 |
+
"Requirement already satisfied: entrypoints in /usr/local/lib/python3.9/dist-packages (from altair>=4.2.0->gradio) (0.4)\n",
|
| 75 |
+
"Requirement already satisfied: fsspec in /usr/local/lib/python3.9/dist-packages (from gradio-client>=0.0.5->gradio) (2023.3.0)\n",
|
| 76 |
+
"Requirement already satisfied: packaging in /usr/local/lib/python3.9/dist-packages (from gradio-client>=0.0.5->gradio) (23.0)\n",
|
| 77 |
+
"Requirement already satisfied: filelock in /usr/local/lib/python3.9/dist-packages (from huggingface-hub>=0.13.0->gradio) (3.10.7)\n",
|
| 78 |
+
"Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.9/dist-packages (from huggingface-hub>=0.13.0->gradio) (4.65.0)\n",
|
| 79 |
+
"Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.9/dist-packages (from markdown-it-py[linkify]>=2.0.0->gradio) (0.1.2)\n",
|
| 80 |
+
"Collecting linkify-it-py<3,>=1\n",
|
| 81 |
+
" Downloading linkify_it_py-2.0.0-py3-none-any.whl (19 kB)\n",
|
| 82 |
+
"Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.9/dist-packages (from pandas->gradio) (2.8.2)\n",
|
| 83 |
+
"Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.9/dist-packages (from pandas->gradio) (2022.7.1)\n",
|
| 84 |
+
"Collecting async-timeout<5.0,>=4.0.0a3\n",
|
| 85 |
+
" Downloading async_timeout-4.0.2-py3-none-any.whl (5.8 kB)\n",
|
| 86 |
+
"Collecting frozenlist>=1.1.1\n",
|
| 87 |
+
" Downloading frozenlist-1.3.3-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (158 kB)\n",
|
| 88 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m158.8/158.8 KB\u001b[0m \u001b[31m17.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 89 |
+
"\u001b[?25hCollecting yarl<2.0,>=1.0\n",
|
| 90 |
+
" Downloading yarl-1.8.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (264 kB)\n",
|
| 91 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m264.6/264.6 KB\u001b[0m \u001b[31m29.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 92 |
+
"\u001b[?25hCollecting aiosignal>=1.1.2\n",
|
| 93 |
+
" Downloading aiosignal-1.3.1-py3-none-any.whl (7.6 kB)\n",
|
| 94 |
+
"Collecting multidict<7.0,>=4.5\n",
|
| 95 |
+
" Downloading multidict-6.0.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (114 kB)\n",
|
| 96 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m114.2/114.2 KB\u001b[0m \u001b[31m10.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 97 |
+
"\u001b[?25hRequirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.9/dist-packages (from aiohttp->gradio) (22.2.0)\n",
|
| 98 |
+
"Requirement already satisfied: charset-normalizer<4.0,>=2.0 in /usr/local/lib/python3.9/dist-packages (from aiohttp->gradio) (2.0.12)\n",
|
| 99 |
+
"Collecting starlette<0.27.0,>=0.26.1\n",
|
| 100 |
+
" Downloading starlette-0.26.1-py3-none-any.whl (66 kB)\n",
|
| 101 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m66.9/66.9 KB\u001b[0m \u001b[31m9.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 102 |
+
"\u001b[?25hRequirement already satisfied: certifi in /usr/local/lib/python3.9/dist-packages (from httpx->gradio) (2022.12.7)\n",
|
| 103 |
+
"Collecting httpcore<0.17.0,>=0.15.0\n",
|
| 104 |
+
" Downloading httpcore-0.16.3-py3-none-any.whl (69 kB)\n",
|
| 105 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m69.6/69.6 KB\u001b[0m \u001b[31m9.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 106 |
+
"\u001b[?25hRequirement already satisfied: sniffio in /usr/local/lib/python3.9/dist-packages (from httpx->gradio) (1.3.0)\n",
|
| 107 |
+
"Collecting rfc3986[idna2008]<2,>=1.3\n",
|
| 108 |
+
" Downloading rfc3986-1.5.0-py2.py3-none-any.whl (31 kB)\n",
|
| 109 |
+
"Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib->gradio) (1.4.4)\n",
|
| 110 |
+
"Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.9/dist-packages (from matplotlib->gradio) (0.11.0)\n",
|
| 111 |
+
"Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib->gradio) (3.0.9)\n",
|
| 112 |
+
"Requirement already satisfied: importlib-resources>=3.2.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib->gradio) (5.12.0)\n",
|
| 113 |
+
"Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib->gradio) (1.0.7)\n",
|
| 114 |
+
"Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib->gradio) (4.39.3)\n",
|
| 115 |
+
"Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.9/dist-packages (from requests->gradio) (1.26.15)\n",
|
| 116 |
+
"Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.9/dist-packages (from requests->gradio) (3.4)\n",
|
| 117 |
+
"Requirement already satisfied: click>=7.0 in /usr/local/lib/python3.9/dist-packages (from uvicorn->gradio) (8.1.3)\n",
|
| 118 |
+
"Collecting h11>=0.8\n",
|
| 119 |
+
" Downloading h11-0.14.0-py3-none-any.whl (58 kB)\n",
|
| 120 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.3/58.3 KB\u001b[0m \u001b[31m7.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 121 |
+
"\u001b[?25hRequirement already satisfied: anyio<5.0,>=3.0 in /usr/local/lib/python3.9/dist-packages (from httpcore<0.17.0,>=0.15.0->httpx->gradio) (3.6.2)\n",
|
| 122 |
+
"Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.9/dist-packages (from importlib-resources>=3.2.0->matplotlib->gradio) (3.15.0)\n",
|
| 123 |
+
"Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.9/dist-packages (from jsonschema>=3.0->altair>=4.2.0->gradio) (0.19.3)\n",
|
| 124 |
+
"Collecting uc-micro-py\n",
|
| 125 |
+
" Downloading uc_micro_py-1.0.1-py3-none-any.whl (6.2 kB)\n",
|
| 126 |
+
"Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.9/dist-packages (from python-dateutil>=2.8.1->pandas->gradio) (1.16.0)\n",
|
| 127 |
+
"Building wheels for collected packages: ffmpy\n",
|
| 128 |
+
" Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
|
| 129 |
+
" Created wheel for ffmpy: filename=ffmpy-0.3.0-py3-none-any.whl size=4707 sha256=6c11ab449511a5b4400565cca1a34e683c2488a9714f17eccad6aec67d058c21\n",
|
| 130 |
+
" Stored in directory: /root/.cache/pip/wheels/91/e2/96/f676aa08bfd789328c6576cd0f1fde4a3d686703bb0c247697\n",
|
| 131 |
+
"Successfully built ffmpy\n",
|
| 132 |
+
"Installing collected packages: rfc3986, pydub, ffmpy, websockets, uc-micro-py, semantic-version, python-multipart, orjson, multidict, h11, frozenlist, async-timeout, aiofiles, yarl, uvicorn, starlette, mdit-py-plugins, linkify-it-py, huggingface-hub, httpcore, aiosignal, httpx, gradio-client, fastapi, aiohttp, gradio\n",
|
| 133 |
+
"Successfully installed aiofiles-23.1.0 aiohttp-3.8.4 aiosignal-1.3.1 async-timeout-4.0.2 fastapi-0.95.0 ffmpy-0.3.0 frozenlist-1.3.3 gradio-3.24.1 gradio-client-0.0.7 h11-0.14.0 httpcore-0.16.3 httpx-0.23.3 huggingface-hub-0.13.3 linkify-it-py-2.0.0 mdit-py-plugins-0.3.3 multidict-6.0.4 orjson-3.8.9 pydub-0.25.1 python-multipart-0.0.6 rfc3986-1.5.0 semantic-version-2.10.0 starlette-0.26.1 uc-micro-py-1.0.1 uvicorn-0.21.1 websockets-11.0 yarl-1.8.2\n"
|
| 134 |
+
]
|
| 135 |
+
}
|
| 136 |
+
],
|
| 137 |
+
"source": [
|
| 138 |
+
"!pip install gradio"
|
| 139 |
+
]
|
| 140 |
+
},
|
| 141 |
+
{
|
| 142 |
+
"cell_type": "code",
|
| 143 |
+
"execution_count": 2,
|
| 144 |
+
"metadata": {
|
| 145 |
+
"colab": {
|
| 146 |
+
"base_uri": "https://localhost:8080/"
|
| 147 |
+
},
|
| 148 |
+
"id": "XTmWAVdr4NKU",
|
| 149 |
+
"outputId": "f0e73bd3-9798-4f22-85d6-d39ea7292061"
|
| 150 |
+
},
|
| 151 |
+
"outputs": [
|
| 152 |
+
{
|
| 153 |
+
"name": "stdout",
|
| 154 |
+
"output_type": "stream",
|
| 155 |
+
"text": [
|
| 156 |
+
"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
|
| 157 |
+
"Collecting transformers\n",
|
| 158 |
+
" Downloading transformers-4.27.4-py3-none-any.whl (6.8 MB)\n",
|
| 159 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.8/6.8 MB\u001b[0m \u001b[31m58.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 160 |
+
"\u001b[?25hRequirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.9/dist-packages (from transformers) (1.22.4)\n",
|
| 161 |
+
"Requirement already satisfied: huggingface-hub<1.0,>=0.11.0 in /usr/local/lib/python3.9/dist-packages (from transformers) (0.13.3)\n",
|
| 162 |
+
"Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.9/dist-packages (from transformers) (2022.10.31)\n",
|
| 163 |
+
"Requirement already satisfied: filelock in /usr/local/lib/python3.9/dist-packages (from transformers) (3.10.7)\n",
|
| 164 |
+
"Requirement already satisfied: requests in /usr/local/lib/python3.9/dist-packages (from transformers) (2.27.1)\n",
|
| 165 |
+
"Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.9/dist-packages (from transformers) (6.0)\n",
|
| 166 |
+
"Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.9/dist-packages (from transformers) (4.65.0)\n",
|
| 167 |
+
"Collecting tokenizers!=0.11.3,<0.14,>=0.11.1\n",
|
| 168 |
+
" Downloading tokenizers-0.13.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.8 MB)\n",
|
| 169 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.8/7.8 MB\u001b[0m \u001b[31m21.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 170 |
+
"\u001b[?25hRequirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.9/dist-packages (from transformers) (23.0)\n",
|
| 171 |
+
"Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.9/dist-packages (from huggingface-hub<1.0,>=0.11.0->transformers) (4.5.0)\n",
|
| 172 |
+
"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.9/dist-packages (from requests->transformers) (2022.12.7)\n",
|
| 173 |
+
"Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.9/dist-packages (from requests->transformers) (3.4)\n",
|
| 174 |
+
"Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.9/dist-packages (from requests->transformers) (2.0.12)\n",
|
| 175 |
+
"Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.9/dist-packages (from requests->transformers) (1.26.15)\n",
|
| 176 |
+
"Installing collected packages: tokenizers, transformers\n",
|
| 177 |
+
"Successfully installed tokenizers-0.13.3 transformers-4.27.4\n"
|
| 178 |
+
]
|
| 179 |
+
}
|
| 180 |
+
],
|
| 181 |
+
"source": [
|
| 182 |
+
"!pip install transformers"
|
| 183 |
+
]
|
| 184 |
+
},
|
| 185 |
+
{
|
| 186 |
+
"cell_type": "code",
|
| 187 |
+
"execution_count": 1,
|
| 188 |
+
"metadata": {
|
| 189 |
+
"colab": {
|
| 190 |
+
"base_uri": "https://localhost:8080/"
|
| 191 |
+
},
|
| 192 |
+
"id": "85RiizMcwM6b",
|
| 193 |
+
"outputId": "c4ff5378-2118-4296-c52e-829a79bfb846"
|
| 194 |
+
},
|
| 195 |
+
"outputs": [
|
| 196 |
+
{
|
| 197 |
+
"name": "stderr",
|
| 198 |
+
"output_type": "stream",
|
| 199 |
+
"text": [
|
| 200 |
+
"[nltk_data] Downloading package punkt to\n",
|
| 201 |
+
"[nltk_data] C:\\Users\\Asus\\AppData\\Roaming\\nltk_data...\n",
|
| 202 |
+
"[nltk_data] Package punkt is already up-to-date!\n",
|
| 203 |
+
"[nltk_data] Downloading package stopwords to\n",
|
| 204 |
+
"[nltk_data] C:\\Users\\Asus\\AppData\\Roaming\\nltk_data...\n",
|
| 205 |
+
"[nltk_data] Package stopwords is already up-to-date!\n"
|
| 206 |
+
]
|
| 207 |
+
}
|
| 208 |
+
],
|
| 209 |
+
"source": [
|
| 210 |
+
"import gradio as gr\n",
|
| 211 |
+
"import pandas as pd\n",
|
| 212 |
+
"from torch import nn\n",
|
| 213 |
+
"from transformers import BertModel\n",
|
| 214 |
+
"from transformers import BertTokenizer\n",
|
| 215 |
+
"from sklearn.metrics import f1_score\n",
|
| 216 |
+
"import torch\n",
|
| 217 |
+
"import nltk\n",
|
| 218 |
+
"nltk.download(['punkt', 'stopwords'])\n",
|
| 219 |
+
"import re"
|
| 220 |
+
]
|
| 221 |
+
},
|
| 222 |
+
{
|
| 223 |
+
"cell_type": "code",
|
| 224 |
+
"execution_count": 2,
|
| 225 |
+
"metadata": {
|
| 226 |
+
"id": "VHMiihOCwvEY"
|
| 227 |
+
},
|
| 228 |
+
"outputs": [],
|
| 229 |
+
"source": [
|
| 230 |
+
"def remove_short_strings(df:pd.DataFrame, string_column:str)->pd.DataFrame:\n",
|
| 231 |
+
" df[string_column] = df[string_column].astype(str)\n",
|
| 232 |
+
" df['length'] = df[string_column].str.len()\n",
|
| 233 |
+
" df = df.drop(df[df['length'] == 1].index)\n",
|
| 234 |
+
" df = df.drop(columns=['length'])\n",
|
| 235 |
+
" return df\n",
|
| 236 |
+
"def remove_one_character_words(row):\n",
|
| 237 |
+
" words = row['text'].split()\n",
|
| 238 |
+
" return ' '.join([word for word in words if len(word) > 1])\n",
|
| 239 |
+
"def ret_list_to_str(liste):\n",
|
| 240 |
+
" return \" \".join (i for i in liste)\n",
|
| 241 |
+
"def preprocess_tweet(tweet):\n",
|
| 242 |
+
" # Convert to lower case\n",
|
| 243 |
+
" tweet = tweet.lower() \n",
|
| 244 |
+
" # Replace repeating characters\n",
|
| 245 |
+
" tweet = re.sub(r'(.)\\1+', r'\\1\\1', tweet)\n",
|
| 246 |
+
" # Remove non-Turkish characters\n",
|
| 247 |
+
" tweet = re.sub(r'[^a-zA-ZçÇğĞıİöÖşŞüÜ\\s]', '', tweet)\n",
|
| 248 |
+
" # Remove extra whitespaces\n",
|
| 249 |
+
" tweet = re.sub(r'\\s+', ' ', tweet).strip()\n",
|
| 250 |
+
" return tweet\n",
|
| 251 |
+
"def cleaning_stopwords(text,stop_words):\n",
|
| 252 |
+
" return \" \".join([word for word in str(text).split() if word not in stop_words])\n",
|
| 253 |
+
"from nltk.corpus import stopwords\n",
|
| 254 |
+
"# Türkçe stop words\n",
|
| 255 |
+
"turkish_stopwords = stopwords.words('turkish')\n",
|
| 256 |
+
"turkish_stopwords.append(\"bir\")\n",
|
| 257 |
+
"turkish_stopwords=set(turkish_stopwords)\n",
|
| 258 |
+
" ##burada saçma kelimeler var bunu kullanmayalım \n",
|
| 259 |
+
"\n",
|
| 260 |
+
"\n",
|
| 261 |
+
"from sklearn import preprocessing\n",
|
| 262 |
+
"from nltk.tokenize import word_tokenize\n",
|
| 263 |
+
"\n",
|
| 264 |
+
"\n",
|
| 265 |
+
"def prep_and_sw_and_tokenize(df):\n",
|
| 266 |
+
"\n",
|
| 267 |
+
" turkish_stopwords = stopwords.words('turkish')\n",
|
| 268 |
+
" turkish_stopwords.append(\"bir\")\n",
|
| 269 |
+
" stop_words=set(turkish_stopwords)\n",
|
| 270 |
+
" df[\"text\"]=df[\"text\"].apply(preprocess_tweet)\n",
|
| 271 |
+
" df['text'] = df[\"text\"].apply(lambda text: cleaning_stopwords(text,stop_words))\n",
|
| 272 |
+
"\n",
|
| 273 |
+
" #df['text'] = df.apply(remove_one_character_words, axis=1)\n",
|
| 274 |
+
"\n",
|
| 275 |
+
"\n",
|
| 276 |
+
" return df"
|
| 277 |
+
]
|
| 278 |
+
},
|
| 279 |
+
{
|
| 280 |
+
"cell_type": "code",
|
| 281 |
+
"execution_count": 3,
|
| 282 |
+
"metadata": {
|
| 283 |
+
"colab": {
|
| 284 |
+
"base_uri": "https://localhost:8080/",
|
| 285 |
+
"height": 113,
|
| 286 |
+
"referenced_widgets": [
|
| 287 |
+
"5f331d1562aa4655a7513ebe96e8e543",
|
| 288 |
+
"5cbc3b58ceb7477aaaf2bb6198f761ae",
|
| 289 |
+
"a75a8d3737c0495fa94b0d37a7ac7cb2",
|
| 290 |
+
"fc163ea867554162918e86086bf16346",
|
| 291 |
+
"16e1c6eff9434dccbe888bf31e846cb3",
|
| 292 |
+
"6e2b50925eba416d977a515a96253c8d",
|
| 293 |
+
"66ce6f6abe62413cafc531ddeab1b234",
|
| 294 |
+
"4c444591789a439ea012c19b9a65943c",
|
| 295 |
+
"e95963b069c0430493068fccad39e549",
|
| 296 |
+
"05ba2899712c41dfbe19b47e310d6f11",
|
| 297 |
+
"f36aadfead2f4ea5bffc5380d1389f83",
|
| 298 |
+
"f7dcb80ead674ea2acca13be918cf29f",
|
| 299 |
+
"6f6bb49fc5cb49b2b61d5da84a85df48",
|
| 300 |
+
"693f00434dd34f6ebbbd3454e20e6f09",
|
| 301 |
+
"182030415ce843bfb55c450688f1173c",
|
| 302 |
+
"26489266a0af48769920239061ea348c",
|
| 303 |
+
"44b676a38c90434c92230d740d8d953b",
|
| 304 |
+
"00a05a5b259d4e9d8219d18f1b6fd9fe",
|
| 305 |
+
"a1e9be8d15fa48bda098fca408cb1dc3",
|
| 306 |
+
"a6aad0e220554fafabc82b1578ea399b",
|
| 307 |
+
"2a6fbcb692504742bd5382bffda82d84",
|
| 308 |
+
"fb886858d4ad4ac0a1d9e8e56941b246",
|
| 309 |
+
"64a97722956b42e78978c674320bffc4",
|
| 310 |
+
"43c825ca23ee4fa4818012fd0d70e7a0",
|
| 311 |
+
"e38e3d64e0f94ff28ce00b145aab4b7d",
|
| 312 |
+
"e70480d3a9d74488b8412057b1c112e7",
|
| 313 |
+
"75f16475449a4af69679a624e7d80b72",
|
| 314 |
+
"b4eb927b4c0143cab3346d4521245103",
|
| 315 |
+
"c4325e65d0b04cc0bce40f6f4a273eb2",
|
| 316 |
+
"90d1288635e84948b23e428c59c140e8",
|
| 317 |
+
"a89f2e52c5ab4210915eec5bb8a67162",
|
| 318 |
+
"fd086c70086d445b9152c65db68ffa40",
|
| 319 |
+
"3c18c7c120c2428595d75cd10bc59ad4"
|
| 320 |
+
]
|
| 321 |
+
},
|
| 322 |
+
"id": "P75bE83_xJEt",
|
| 323 |
+
"outputId": "9db8a1e1-33ca-47fc-875f-ce13480e4209"
|
| 324 |
+
},
|
| 325 |
+
"outputs": [],
|
| 326 |
+
"source": [
|
| 327 |
+
"\n",
|
| 328 |
+
"tokenizer = BertTokenizer.from_pretrained(\"dbmdz/bert-base-turkish-128k-uncased\")\n",
|
| 329 |
+
"class BertClassifierConv1D(nn.Module):\n",
|
| 330 |
+
" def __init__(self, dropout=0.5, num_classes=5):\n",
|
| 331 |
+
" super(BertClassifierConv1D, self).__init__()\n",
|
| 332 |
+
" \n",
|
| 333 |
+
" self.bert = BertModel.from_pretrained('dbmdz/bert-base-turkish-128k-uncased', return_dict=True)\n",
|
| 334 |
+
" self.conv1d = nn.Conv1d(in_channels=self.bert.config.hidden_size, out_channels=128, kernel_size=5)\n",
|
| 335 |
+
" self.bilstm = nn.LSTM(input_size=128, hidden_size=64, num_layers=1, bidirectional=True, batch_first=True)\n",
|
| 336 |
+
" self.dropout = nn.Dropout(dropout)\n",
|
| 337 |
+
" self.linear = nn.Linear(128, num_classes)\n",
|
| 338 |
+
"\n",
|
| 339 |
+
" def forward(self, input_id, mask):\n",
|
| 340 |
+
" output = self.bert(input_ids=input_id, attention_mask=mask).last_hidden_state\n",
|
| 341 |
+
" output = output.permute(0, 2, 1) # swap dimensions to prepare for Conv1d layer\n",
|
| 342 |
+
" output = self.conv1d(output)\n",
|
| 343 |
+
" output, _ = self.bilstm(output.transpose(1, 2))\n",
|
| 344 |
+
" output = self.dropout(output)\n",
|
| 345 |
+
" output = self.linear(output.mean(dim=1))\n",
|
| 346 |
+
" return output\n",
|
| 347 |
+
"class Dataset(torch.utils.data.Dataset):\n",
|
| 348 |
+
" def __init__(self, df):\n",
|
| 349 |
+
" self.texts = [tokenizer(text, padding='max_length', max_length=512, truncation=True, return_tensors=\"pt\") for text in df]\n",
|
| 350 |
+
"\n",
|
| 351 |
+
" def __len__(self):\n",
|
| 352 |
+
" return len(self.texts)\n",
|
| 353 |
+
"\n",
|
| 354 |
+
" def __getitem__(self, idx):\n",
|
| 355 |
+
" batch_texts = self.texts[idx]\n",
|
| 356 |
+
" return batch_texts\n",
|
| 357 |
+
"def evaluate(model, test_data):\n",
|
| 358 |
+
"\n",
|
| 359 |
+
" test = Dataset(test_data)\n",
|
| 360 |
+
"\n",
|
| 361 |
+
" test_dataloader = torch.utils.data.DataLoader(test, batch_size=32)\n",
|
| 362 |
+
"\n",
|
| 363 |
+
" #use_cuda = torch.cuda.is_available()\n",
|
| 364 |
+
" #device = torch.device(\"cuda\" if use_cuda else \"cpu\")\n",
|
| 365 |
+
" device= torch.device(\"cpu\")\n",
|
| 366 |
+
"\n",
|
| 367 |
+
" #if use_cuda:\n",
|
| 368 |
+
"\n",
|
| 369 |
+
" # model = model.cuda()\n",
|
| 370 |
+
"\n",
|
| 371 |
+
" total_acc_test = 0\n",
|
| 372 |
+
" output_indices = []\n",
|
| 373 |
+
" with torch.no_grad():\n",
|
| 374 |
+
"\n",
|
| 375 |
+
" for test_input in test_dataloader:\n",
|
| 376 |
+
"\n",
|
| 377 |
+
" mask = test_input['attention_mask'].to(device)\n",
|
| 378 |
+
" input_id = test_input['input_ids'].squeeze(1).to(device)\n",
|
| 379 |
+
"\n",
|
| 380 |
+
" output = model(input_id, mask)\n",
|
| 381 |
+
" \n",
|
| 382 |
+
"\n",
|
| 383 |
+
" batch_indices = output.argmax(dim=1).tolist()\n",
|
| 384 |
+
" output_indices.extend(batch_indices)\n",
|
| 385 |
+
"\n",
|
| 386 |
+
" \n",
|
| 387 |
+
" \n",
|
| 388 |
+
" return output_indices\n"
|
| 389 |
+
]
|
| 390 |
+
},
|
| 391 |
+
{
|
| 392 |
+
"cell_type": "code",
|
| 393 |
+
"execution_count": 4,
|
| 394 |
+
"metadata": {
|
| 395 |
+
"id": "l_Gfr3A_wSBm"
|
| 396 |
+
},
|
| 397 |
+
"outputs": [],
|
| 398 |
+
"source": [
|
| 399 |
+
"def auth(username, password):\n",
|
| 400 |
+
" if username == \"Hive_Hereos\" and password == \"Y2IB3HV8GBXED00S\":\n",
|
| 401 |
+
" return True\n",
|
| 402 |
+
" else:\n",
|
| 403 |
+
" return False\n"
|
| 404 |
+
]
|
| 405 |
+
},
|
| 406 |
+
{
|
| 407 |
+
"cell_type": "code",
|
| 408 |
+
"execution_count": 5,
|
| 409 |
+
"metadata": {},
|
| 410 |
+
"outputs": [
|
| 411 |
+
{
|
| 412 |
+
"name": "stderr",
|
| 413 |
+
"output_type": "stream",
|
| 414 |
+
"text": [
|
| 415 |
+
"Some weights of the model checkpoint at dbmdz/bert-base-turkish-128k-uncased were not used when initializing BertModel: ['cls.predictions.transform.dense.weight', 'cls.predictions.bias', 'cls.predictions.decoder.bias', 'cls.seq_relationship.bias', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.dense.bias', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.decoder.weight', 'cls.seq_relationship.weight']\n",
|
| 416 |
+
"- This IS expected if you are initializing BertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
|
| 417 |
+
"- This IS NOT expected if you are initializing BertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n"
|
| 418 |
+
]
|
| 419 |
+
},
|
| 420 |
+
{
|
| 421 |
+
"data": {
|
| 422 |
+
"text/plain": [
|
| 423 |
+
"<All keys matched successfully>"
|
| 424 |
+
]
|
| 425 |
+
},
|
| 426 |
+
"execution_count": 5,
|
| 427 |
+
"metadata": {},
|
| 428 |
+
"output_type": "execute_result"
|
| 429 |
+
}
|
| 430 |
+
],
|
| 431 |
+
"source": [
|
| 432 |
+
"global model\n",
|
| 433 |
+
"model =BertClassifierConv1D()\n",
|
| 434 |
+
"\n",
|
| 435 |
+
"model.load_state_dict(torch.load(r\"sontotalmodel_finallll.pt\", map_location=torch.device('cpu')))\n"
|
| 436 |
+
]
|
| 437 |
+
},
|
| 438 |
+
{
|
| 439 |
+
"cell_type": "code",
|
| 440 |
+
"execution_count": 6,
|
| 441 |
+
"metadata": {
|
| 442 |
+
"id": "TafHYRYDwcdn"
|
| 443 |
+
},
|
| 444 |
+
"outputs": [],
|
| 445 |
+
"source": [
|
| 446 |
+
"import logging\n",
|
| 447 |
+
"logging.basicConfig(filename=r'app.log', filemode='w', format='%(asctime)s - %(message)s', level=logging.INFO)\n",
|
| 448 |
+
"\n",
|
| 449 |
+
"\n",
|
| 450 |
+
"def predict(df):\n",
|
| 451 |
+
" # TODO:\n",
|
| 452 |
+
" df[\"offensive\"] = 1 \n",
|
| 453 |
+
" df[\"target\"] = None\n",
|
| 454 |
+
" # ***************************\n",
|
| 455 |
+
" try:\n",
|
| 456 |
+
" # WRITE YOUR INFERENCE STEPS BELOW # HERE\n",
|
| 457 |
+
" text=df[\"text\"]\n",
|
| 458 |
+
" df=prep_and_sw_and_tokenize(df)\n",
|
| 459 |
+
" #df.to_csv(\"preprocess.csv\", index=False, sep=\"|\")\n",
|
| 460 |
+
" labels = {'INSULT':0,\n",
|
| 461 |
+
" 'OTHER':1,\n",
|
| 462 |
+
" 'PROFANITY':2,\n",
|
| 463 |
+
" 'RACIST':3,\n",
|
| 464 |
+
" 'SEXIST':4\n",
|
| 465 |
+
" }\n",
|
| 466 |
+
" logging.info(\"Başlıyoruz\")\n",
|
| 467 |
+
" \n",
|
| 468 |
+
" logging.info(\"Model yüklendi\")\n",
|
| 469 |
+
" logging.info(df.text)\n",
|
| 470 |
+
" a=evaluate(model, df[\"text\"])\n",
|
| 471 |
+
" \n",
|
| 472 |
+
" test_labels=[]\n",
|
| 473 |
+
" for number in a:\n",
|
| 474 |
+
" label = list(labels.keys())[list(labels.values()).index(number)] # Sayıyı etikete dönüştürüyoruz.\n",
|
| 475 |
+
" test_labels.append(label) # Yeni etiketi listeye ekliyoruz.\n",
|
| 476 |
+
" df[\"target\"]=test_labels\n",
|
| 477 |
+
" \n",
|
| 478 |
+
" for index, row in df.iterrows():\n",
|
| 479 |
+
" if row['target'] == 'OTHER':\n",
|
| 480 |
+
" df.at[index, 'offensive'] = 0\n",
|
| 481 |
+
" df[\"text\"]=text\n",
|
| 482 |
+
" except Exception as e:\n",
|
| 483 |
+
" logging.error(\"Error occurred\", exc_info=True) \n",
|
| 484 |
+
" raise e\n",
|
| 485 |
+
" #\n",
|
| 486 |
+
" # *********** END ***********\n",
|
| 487 |
+
"\n",
|
| 488 |
+
"\n",
|
| 489 |
+
" return df\n"
|
| 490 |
+
]
|
| 491 |
+
},
|
| 492 |
+
{
|
| 493 |
+
"cell_type": "code",
|
| 494 |
+
"execution_count": 7,
|
| 495 |
+
"metadata": {
|
| 496 |
+
"id": "tFwQjDPowfWs"
|
| 497 |
+
},
|
| 498 |
+
"outputs": [],
|
| 499 |
+
"source": [
|
| 500 |
+
"def get_file(file):\n",
|
| 501 |
+
" output_file = \"output_Hive_Hereos.csv\"\n",
|
| 502 |
+
"\n",
|
| 503 |
+
" # For windows users, replace path seperator\n",
|
| 504 |
+
" file_name = file.name.replace(\"\\\\\", \"/\")\n",
|
| 505 |
+
"\n",
|
| 506 |
+
" df = pd.read_csv(file_name, sep=\"|\")\n",
|
| 507 |
+
"\n",
|
| 508 |
+
" predict(df)\n",
|
| 509 |
+
" df.to_csv(output_file, index=False, sep=\"|\")\n",
|
| 510 |
+
" return (output_file)\n"
|
| 511 |
+
]
|
| 512 |
+
},
|
| 513 |
+
{
|
| 514 |
+
"cell_type": "code",
|
| 515 |
+
"execution_count": null,
|
| 516 |
+
"metadata": {
|
| 517 |
+
"colab": {
|
| 518 |
+
"base_uri": "https://localhost:8080/"
|
| 519 |
+
},
|
| 520 |
+
"id": "PQI8hfLxwjEX",
|
| 521 |
+
"outputId": "198e3795-5917-4a91-ed21-8ebccb0da373",
|
| 522 |
+
"scrolled": true
|
| 523 |
+
},
|
| 524 |
+
"outputs": [
|
| 525 |
+
{
|
| 526 |
+
"name": "stdout",
|
| 527 |
+
"output_type": "stream",
|
| 528 |
+
"text": [
|
| 529 |
+
"Running on local URL: http://127.0.0.1:7860\n",
|
| 530 |
+
"Running on public URL: https://d7857c2e67677f4433.gradio.live\n",
|
| 531 |
+
"\n",
|
| 532 |
+
"This share link expires in 72 hours. For free permanent hosting and GPU upgrades (NEW!), check out Spaces: https://huggingface.co/spaces\n"
|
| 533 |
+
]
|
| 534 |
+
}
|
| 535 |
+
],
|
| 536 |
+
"source": [
|
| 537 |
+
"# Launch the interface with user password\n",
|
| 538 |
+
"iface = gr.Interface(get_file, \"file\", \"file\")\n",
|
| 539 |
+
"\n",
|
| 540 |
+
"if __name__ == \"__main__\":\n",
|
| 541 |
+
" iface.launch(share=True, auth=auth,debug=True)"
|
| 542 |
+
]
|
| 543 |
+
},
|
| 544 |
+
{
|
| 545 |
+
"cell_type": "code",
|
| 546 |
+
"execution_count": 32,
|
| 547 |
+
"metadata": {
|
| 548 |
+
"id": "pdgqxuRE5Gyr"
|
| 549 |
+
},
|
| 550 |
+
"outputs": [
|
| 551 |
+
{
|
| 552 |
+
"name": "stdout",
|
| 553 |
+
"output_type": "stream",
|
| 554 |
+
"text": [
|
| 555 |
+
"Closing server running on port: 7860\n"
|
| 556 |
+
]
|
| 557 |
+
}
|
| 558 |
+
],
|
| 559 |
+
"source": [
|
| 560 |
+
"iface.close()"
|
| 561 |
+
]
|
| 562 |
+
},
|
| 563 |
+
{
|
| 564 |
+
"cell_type": "code",
|
| 565 |
+
"execution_count": 82,
|
| 566 |
+
"metadata": {},
|
| 567 |
+
"outputs": [],
|
| 568 |
+
"source": [
|
| 569 |
+
"df = pd.read_csv(r\"C:\\Users\\Asus\\Desktop\\teknofest\\codes\\datas\\teknofest_train_final.csv\", sep=\"|\")\n",
|
| 570 |
+
"df=df[1:16]\n",
|
| 571 |
+
"df=df[[\"id\",\"text\"]]\n",
|
| 572 |
+
"df.to_csv(r\"C:\\Users\\Asus\\Desktop\\teknofest\\codes\\datas\\deneme_test.csv\", index=False, sep=\"|\")"
|
| 573 |
+
]
|
| 574 |
+
},
|
| 575 |
+
{
|
| 576 |
+
"cell_type": "code",
|
| 577 |
+
"execution_count": null,
|
| 578 |
+
"metadata": {},
|
| 579 |
+
"outputs": [],
|
| 580 |
+
"source": [
|
| 581 |
+
"import session_info\n",
|
| 582 |
+
"session_info.show()"
|
| 583 |
+
]
|
| 584 |
+
},
|
| 585 |
+
{
|
| 586 |
+
"cell_type": "code",
|
| 587 |
+
"execution_count": null,
|
| 588 |
+
"metadata": {},
|
| 589 |
+
"outputs": [],
|
| 590 |
+
"source": []
|
| 591 |
+
}
|
| 592 |
+
],
|
| 593 |
+
"metadata": {
|
| 594 |
+
"accelerator": "GPU",
|
| 595 |
+
"colab": {
|
| 596 |
+
"provenance": []
|
| 597 |
+
},
|
| 598 |
+
"gpuClass": "standard",
|
| 599 |
+
"kernelspec": {
|
| 600 |
+
"display_name": "Python 3 (ipykernel)",
|
| 601 |
+
"language": "python",
|
| 602 |
+
"name": "python3"
|
| 603 |
+
},
|
| 604 |
+
"language_info": {
|
| 605 |
+
"codemirror_mode": {
|
| 606 |
+
"name": "ipython",
|
| 607 |
+
"version": 3
|
| 608 |
+
},
|
| 609 |
+
"file_extension": ".py",
|
| 610 |
+
"mimetype": "text/x-python",
|
| 611 |
+
"name": "python",
|
| 612 |
+
"nbconvert_exporter": "python",
|
| 613 |
+
"pygments_lexer": "ipython3",
|
| 614 |
+
"version": "3.9.16"
|
| 615 |
+
},
|
| 616 |
+
"widgets": {
|
| 617 |
+
"application/vnd.jupyter.widget-state+json": {
|
| 618 |
+
"00a05a5b259d4e9d8219d18f1b6fd9fe": {
|
| 619 |
+
"model_module": "@jupyter-widgets/controls",
|
| 620 |
+
"model_module_version": "1.5.0",
|
| 621 |
+
"model_name": "DescriptionStyleModel",
|
| 622 |
+
"state": {
|
| 623 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 624 |
+
"_model_module_version": "1.5.0",
|
| 625 |
+
"_model_name": "DescriptionStyleModel",
|
| 626 |
+
"_view_count": null,
|
| 627 |
+
"_view_module": "@jupyter-widgets/base",
|
| 628 |
+
"_view_module_version": "1.2.0",
|
| 629 |
+
"_view_name": "StyleView",
|
| 630 |
+
"description_width": ""
|
| 631 |
+
}
|
| 632 |
+
},
|
| 633 |
+
"05ba2899712c41dfbe19b47e310d6f11": {
|
| 634 |
+
"model_module": "@jupyter-widgets/base",
|
| 635 |
+
"model_module_version": "1.2.0",
|
| 636 |
+
"model_name": "LayoutModel",
|
| 637 |
+
"state": {
|
| 638 |
+
"_model_module": "@jupyter-widgets/base",
|
| 639 |
+
"_model_module_version": "1.2.0",
|
| 640 |
+
"_model_name": "LayoutModel",
|
| 641 |
+
"_view_count": null,
|
| 642 |
+
"_view_module": "@jupyter-widgets/base",
|
| 643 |
+
"_view_module_version": "1.2.0",
|
| 644 |
+
"_view_name": "LayoutView",
|
| 645 |
+
"align_content": null,
|
| 646 |
+
"align_items": null,
|
| 647 |
+
"align_self": null,
|
| 648 |
+
"border": null,
|
| 649 |
+
"bottom": null,
|
| 650 |
+
"display": null,
|
| 651 |
+
"flex": null,
|
| 652 |
+
"flex_flow": null,
|
| 653 |
+
"grid_area": null,
|
| 654 |
+
"grid_auto_columns": null,
|
| 655 |
+
"grid_auto_flow": null,
|
| 656 |
+
"grid_auto_rows": null,
|
| 657 |
+
"grid_column": null,
|
| 658 |
+
"grid_gap": null,
|
| 659 |
+
"grid_row": null,
|
| 660 |
+
"grid_template_areas": null,
|
| 661 |
+
"grid_template_columns": null,
|
| 662 |
+
"grid_template_rows": null,
|
| 663 |
+
"height": null,
|
| 664 |
+
"justify_content": null,
|
| 665 |
+
"justify_items": null,
|
| 666 |
+
"left": null,
|
| 667 |
+
"margin": null,
|
| 668 |
+
"max_height": null,
|
| 669 |
+
"max_width": null,
|
| 670 |
+
"min_height": null,
|
| 671 |
+
"min_width": null,
|
| 672 |
+
"object_fit": null,
|
| 673 |
+
"object_position": null,
|
| 674 |
+
"order": null,
|
| 675 |
+
"overflow": null,
|
| 676 |
+
"overflow_x": null,
|
| 677 |
+
"overflow_y": null,
|
| 678 |
+
"padding": null,
|
| 679 |
+
"right": null,
|
| 680 |
+
"top": null,
|
| 681 |
+
"visibility": null,
|
| 682 |
+
"width": null
|
| 683 |
+
}
|
| 684 |
+
},
|
| 685 |
+
"16e1c6eff9434dccbe888bf31e846cb3": {
|
| 686 |
+
"model_module": "@jupyter-widgets/base",
|
| 687 |
+
"model_module_version": "1.2.0",
|
| 688 |
+
"model_name": "LayoutModel",
|
| 689 |
+
"state": {
|
| 690 |
+
"_model_module": "@jupyter-widgets/base",
|
| 691 |
+
"_model_module_version": "1.2.0",
|
| 692 |
+
"_model_name": "LayoutModel",
|
| 693 |
+
"_view_count": null,
|
| 694 |
+
"_view_module": "@jupyter-widgets/base",
|
| 695 |
+
"_view_module_version": "1.2.0",
|
| 696 |
+
"_view_name": "LayoutView",
|
| 697 |
+
"align_content": null,
|
| 698 |
+
"align_items": null,
|
| 699 |
+
"align_self": null,
|
| 700 |
+
"border": null,
|
| 701 |
+
"bottom": null,
|
| 702 |
+
"display": null,
|
| 703 |
+
"flex": null,
|
| 704 |
+
"flex_flow": null,
|
| 705 |
+
"grid_area": null,
|
| 706 |
+
"grid_auto_columns": null,
|
| 707 |
+
"grid_auto_flow": null,
|
| 708 |
+
"grid_auto_rows": null,
|
| 709 |
+
"grid_column": null,
|
| 710 |
+
"grid_gap": null,
|
| 711 |
+
"grid_row": null,
|
| 712 |
+
"grid_template_areas": null,
|
| 713 |
+
"grid_template_columns": null,
|
| 714 |
+
"grid_template_rows": null,
|
| 715 |
+
"height": null,
|
| 716 |
+
"justify_content": null,
|
| 717 |
+
"justify_items": null,
|
| 718 |
+
"left": null,
|
| 719 |
+
"margin": null,
|
| 720 |
+
"max_height": null,
|
| 721 |
+
"max_width": null,
|
| 722 |
+
"min_height": null,
|
| 723 |
+
"min_width": null,
|
| 724 |
+
"object_fit": null,
|
| 725 |
+
"object_position": null,
|
| 726 |
+
"order": null,
|
| 727 |
+
"overflow": null,
|
| 728 |
+
"overflow_x": null,
|
| 729 |
+
"overflow_y": null,
|
| 730 |
+
"padding": null,
|
| 731 |
+
"right": null,
|
| 732 |
+
"top": null,
|
| 733 |
+
"visibility": null,
|
| 734 |
+
"width": null
|
| 735 |
+
}
|
| 736 |
+
},
|
| 737 |
+
"182030415ce843bfb55c450688f1173c": {
|
| 738 |
+
"model_module": "@jupyter-widgets/controls",
|
| 739 |
+
"model_module_version": "1.5.0",
|
| 740 |
+
"model_name": "HTMLModel",
|
| 741 |
+
"state": {
|
| 742 |
+
"_dom_classes": [],
|
| 743 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 744 |
+
"_model_module_version": "1.5.0",
|
| 745 |
+
"_model_name": "HTMLModel",
|
| 746 |
+
"_view_count": null,
|
| 747 |
+
"_view_module": "@jupyter-widgets/controls",
|
| 748 |
+
"_view_module_version": "1.5.0",
|
| 749 |
+
"_view_name": "HTMLView",
|
| 750 |
+
"description": "",
|
| 751 |
+
"description_tooltip": null,
|
| 752 |
+
"layout": "IPY_MODEL_2a6fbcb692504742bd5382bffda82d84",
|
| 753 |
+
"placeholder": "",
|
| 754 |
+
"style": "IPY_MODEL_fb886858d4ad4ac0a1d9e8e56941b246",
|
| 755 |
+
"value": " 59.0/59.0 [00:00<00:00, 588B/s]"
|
| 756 |
+
}
|
| 757 |
+
},
|
| 758 |
+
"26489266a0af48769920239061ea348c": {
|
| 759 |
+
"model_module": "@jupyter-widgets/base",
|
| 760 |
+
"model_module_version": "1.2.0",
|
| 761 |
+
"model_name": "LayoutModel",
|
| 762 |
+
"state": {
|
| 763 |
+
"_model_module": "@jupyter-widgets/base",
|
| 764 |
+
"_model_module_version": "1.2.0",
|
| 765 |
+
"_model_name": "LayoutModel",
|
| 766 |
+
"_view_count": null,
|
| 767 |
+
"_view_module": "@jupyter-widgets/base",
|
| 768 |
+
"_view_module_version": "1.2.0",
|
| 769 |
+
"_view_name": "LayoutView",
|
| 770 |
+
"align_content": null,
|
| 771 |
+
"align_items": null,
|
| 772 |
+
"align_self": null,
|
| 773 |
+
"border": null,
|
| 774 |
+
"bottom": null,
|
| 775 |
+
"display": null,
|
| 776 |
+
"flex": null,
|
| 777 |
+
"flex_flow": null,
|
| 778 |
+
"grid_area": null,
|
| 779 |
+
"grid_auto_columns": null,
|
| 780 |
+
"grid_auto_flow": null,
|
| 781 |
+
"grid_auto_rows": null,
|
| 782 |
+
"grid_column": null,
|
| 783 |
+
"grid_gap": null,
|
| 784 |
+
"grid_row": null,
|
| 785 |
+
"grid_template_areas": null,
|
| 786 |
+
"grid_template_columns": null,
|
| 787 |
+
"grid_template_rows": null,
|
| 788 |
+
"height": null,
|
| 789 |
+
"justify_content": null,
|
| 790 |
+
"justify_items": null,
|
| 791 |
+
"left": null,
|
| 792 |
+
"margin": null,
|
| 793 |
+
"max_height": null,
|
| 794 |
+
"max_width": null,
|
| 795 |
+
"min_height": null,
|
| 796 |
+
"min_width": null,
|
| 797 |
+
"object_fit": null,
|
| 798 |
+
"object_position": null,
|
| 799 |
+
"order": null,
|
| 800 |
+
"overflow": null,
|
| 801 |
+
"overflow_x": null,
|
| 802 |
+
"overflow_y": null,
|
| 803 |
+
"padding": null,
|
| 804 |
+
"right": null,
|
| 805 |
+
"top": null,
|
| 806 |
+
"visibility": null,
|
| 807 |
+
"width": null
|
| 808 |
+
}
|
| 809 |
+
},
|
| 810 |
+
"2a6fbcb692504742bd5382bffda82d84": {
|
| 811 |
+
"model_module": "@jupyter-widgets/base",
|
| 812 |
+
"model_module_version": "1.2.0",
|
| 813 |
+
"model_name": "LayoutModel",
|
| 814 |
+
"state": {
|
| 815 |
+
"_model_module": "@jupyter-widgets/base",
|
| 816 |
+
"_model_module_version": "1.2.0",
|
| 817 |
+
"_model_name": "LayoutModel",
|
| 818 |
+
"_view_count": null,
|
| 819 |
+
"_view_module": "@jupyter-widgets/base",
|
| 820 |
+
"_view_module_version": "1.2.0",
|
| 821 |
+
"_view_name": "LayoutView",
|
| 822 |
+
"align_content": null,
|
| 823 |
+
"align_items": null,
|
| 824 |
+
"align_self": null,
|
| 825 |
+
"border": null,
|
| 826 |
+
"bottom": null,
|
| 827 |
+
"display": null,
|
| 828 |
+
"flex": null,
|
| 829 |
+
"flex_flow": null,
|
| 830 |
+
"grid_area": null,
|
| 831 |
+
"grid_auto_columns": null,
|
| 832 |
+
"grid_auto_flow": null,
|
| 833 |
+
"grid_auto_rows": null,
|
| 834 |
+
"grid_column": null,
|
| 835 |
+
"grid_gap": null,
|
| 836 |
+
"grid_row": null,
|
| 837 |
+
"grid_template_areas": null,
|
| 838 |
+
"grid_template_columns": null,
|
| 839 |
+
"grid_template_rows": null,
|
| 840 |
+
"height": null,
|
| 841 |
+
"justify_content": null,
|
| 842 |
+
"justify_items": null,
|
| 843 |
+
"left": null,
|
| 844 |
+
"margin": null,
|
| 845 |
+
"max_height": null,
|
| 846 |
+
"max_width": null,
|
| 847 |
+
"min_height": null,
|
| 848 |
+
"min_width": null,
|
| 849 |
+
"object_fit": null,
|
| 850 |
+
"object_position": null,
|
| 851 |
+
"order": null,
|
| 852 |
+
"overflow": null,
|
| 853 |
+
"overflow_x": null,
|
| 854 |
+
"overflow_y": null,
|
| 855 |
+
"padding": null,
|
| 856 |
+
"right": null,
|
| 857 |
+
"top": null,
|
| 858 |
+
"visibility": null,
|
| 859 |
+
"width": null
|
| 860 |
+
}
|
| 861 |
+
},
|
| 862 |
+
"3c18c7c120c2428595d75cd10bc59ad4": {
|
| 863 |
+
"model_module": "@jupyter-widgets/controls",
|
| 864 |
+
"model_module_version": "1.5.0",
|
| 865 |
+
"model_name": "DescriptionStyleModel",
|
| 866 |
+
"state": {
|
| 867 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 868 |
+
"_model_module_version": "1.5.0",
|
| 869 |
+
"_model_name": "DescriptionStyleModel",
|
| 870 |
+
"_view_count": null,
|
| 871 |
+
"_view_module": "@jupyter-widgets/base",
|
| 872 |
+
"_view_module_version": "1.2.0",
|
| 873 |
+
"_view_name": "StyleView",
|
| 874 |
+
"description_width": ""
|
| 875 |
+
}
|
| 876 |
+
},
|
| 877 |
+
"43c825ca23ee4fa4818012fd0d70e7a0": {
|
| 878 |
+
"model_module": "@jupyter-widgets/controls",
|
| 879 |
+
"model_module_version": "1.5.0",
|
| 880 |
+
"model_name": "HTMLModel",
|
| 881 |
+
"state": {
|
| 882 |
+
"_dom_classes": [],
|
| 883 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 884 |
+
"_model_module_version": "1.5.0",
|
| 885 |
+
"_model_name": "HTMLModel",
|
| 886 |
+
"_view_count": null,
|
| 887 |
+
"_view_module": "@jupyter-widgets/controls",
|
| 888 |
+
"_view_module_version": "1.5.0",
|
| 889 |
+
"_view_name": "HTMLView",
|
| 890 |
+
"description": "",
|
| 891 |
+
"description_tooltip": null,
|
| 892 |
+
"layout": "IPY_MODEL_b4eb927b4c0143cab3346d4521245103",
|
| 893 |
+
"placeholder": "",
|
| 894 |
+
"style": "IPY_MODEL_c4325e65d0b04cc0bce40f6f4a273eb2",
|
| 895 |
+
"value": "Downloading (…)lve/main/config.json: 100%"
|
| 896 |
+
}
|
| 897 |
+
},
|
| 898 |
+
"44b676a38c90434c92230d740d8d953b": {
|
| 899 |
+
"model_module": "@jupyter-widgets/base",
|
| 900 |
+
"model_module_version": "1.2.0",
|
| 901 |
+
"model_name": "LayoutModel",
|
| 902 |
+
"state": {
|
| 903 |
+
"_model_module": "@jupyter-widgets/base",
|
| 904 |
+
"_model_module_version": "1.2.0",
|
| 905 |
+
"_model_name": "LayoutModel",
|
| 906 |
+
"_view_count": null,
|
| 907 |
+
"_view_module": "@jupyter-widgets/base",
|
| 908 |
+
"_view_module_version": "1.2.0",
|
| 909 |
+
"_view_name": "LayoutView",
|
| 910 |
+
"align_content": null,
|
| 911 |
+
"align_items": null,
|
| 912 |
+
"align_self": null,
|
| 913 |
+
"border": null,
|
| 914 |
+
"bottom": null,
|
| 915 |
+
"display": null,
|
| 916 |
+
"flex": null,
|
| 917 |
+
"flex_flow": null,
|
| 918 |
+
"grid_area": null,
|
| 919 |
+
"grid_auto_columns": null,
|
| 920 |
+
"grid_auto_flow": null,
|
| 921 |
+
"grid_auto_rows": null,
|
| 922 |
+
"grid_column": null,
|
| 923 |
+
"grid_gap": null,
|
| 924 |
+
"grid_row": null,
|
| 925 |
+
"grid_template_areas": null,
|
| 926 |
+
"grid_template_columns": null,
|
| 927 |
+
"grid_template_rows": null,
|
| 928 |
+
"height": null,
|
| 929 |
+
"justify_content": null,
|
| 930 |
+
"justify_items": null,
|
| 931 |
+
"left": null,
|
| 932 |
+
"margin": null,
|
| 933 |
+
"max_height": null,
|
| 934 |
+
"max_width": null,
|
| 935 |
+
"min_height": null,
|
| 936 |
+
"min_width": null,
|
| 937 |
+
"object_fit": null,
|
| 938 |
+
"object_position": null,
|
| 939 |
+
"order": null,
|
| 940 |
+
"overflow": null,
|
| 941 |
+
"overflow_x": null,
|
| 942 |
+
"overflow_y": null,
|
| 943 |
+
"padding": null,
|
| 944 |
+
"right": null,
|
| 945 |
+
"top": null,
|
| 946 |
+
"visibility": null,
|
| 947 |
+
"width": null
|
| 948 |
+
}
|
| 949 |
+
},
|
| 950 |
+
"4c444591789a439ea012c19b9a65943c": {
|
| 951 |
+
"model_module": "@jupyter-widgets/base",
|
| 952 |
+
"model_module_version": "1.2.0",
|
| 953 |
+
"model_name": "LayoutModel",
|
| 954 |
+
"state": {
|
| 955 |
+
"_model_module": "@jupyter-widgets/base",
|
| 956 |
+
"_model_module_version": "1.2.0",
|
| 957 |
+
"_model_name": "LayoutModel",
|
| 958 |
+
"_view_count": null,
|
| 959 |
+
"_view_module": "@jupyter-widgets/base",
|
| 960 |
+
"_view_module_version": "1.2.0",
|
| 961 |
+
"_view_name": "LayoutView",
|
| 962 |
+
"align_content": null,
|
| 963 |
+
"align_items": null,
|
| 964 |
+
"align_self": null,
|
| 965 |
+
"border": null,
|
| 966 |
+
"bottom": null,
|
| 967 |
+
"display": null,
|
| 968 |
+
"flex": null,
|
| 969 |
+
"flex_flow": null,
|
| 970 |
+
"grid_area": null,
|
| 971 |
+
"grid_auto_columns": null,
|
| 972 |
+
"grid_auto_flow": null,
|
| 973 |
+
"grid_auto_rows": null,
|
| 974 |
+
"grid_column": null,
|
| 975 |
+
"grid_gap": null,
|
| 976 |
+
"grid_row": null,
|
| 977 |
+
"grid_template_areas": null,
|
| 978 |
+
"grid_template_columns": null,
|
| 979 |
+
"grid_template_rows": null,
|
| 980 |
+
"height": null,
|
| 981 |
+
"justify_content": null,
|
| 982 |
+
"justify_items": null,
|
| 983 |
+
"left": null,
|
| 984 |
+
"margin": null,
|
| 985 |
+
"max_height": null,
|
| 986 |
+
"max_width": null,
|
| 987 |
+
"min_height": null,
|
| 988 |
+
"min_width": null,
|
| 989 |
+
"object_fit": null,
|
| 990 |
+
"object_position": null,
|
| 991 |
+
"order": null,
|
| 992 |
+
"overflow": null,
|
| 993 |
+
"overflow_x": null,
|
| 994 |
+
"overflow_y": null,
|
| 995 |
+
"padding": null,
|
| 996 |
+
"right": null,
|
| 997 |
+
"top": null,
|
| 998 |
+
"visibility": null,
|
| 999 |
+
"width": null
|
| 1000 |
+
}
|
| 1001 |
+
},
|
| 1002 |
+
"5cbc3b58ceb7477aaaf2bb6198f761ae": {
|
| 1003 |
+
"model_module": "@jupyter-widgets/controls",
|
| 1004 |
+
"model_module_version": "1.5.0",
|
| 1005 |
+
"model_name": "HTMLModel",
|
| 1006 |
+
"state": {
|
| 1007 |
+
"_dom_classes": [],
|
| 1008 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 1009 |
+
"_model_module_version": "1.5.0",
|
| 1010 |
+
"_model_name": "HTMLModel",
|
| 1011 |
+
"_view_count": null,
|
| 1012 |
+
"_view_module": "@jupyter-widgets/controls",
|
| 1013 |
+
"_view_module_version": "1.5.0",
|
| 1014 |
+
"_view_name": "HTMLView",
|
| 1015 |
+
"description": "",
|
| 1016 |
+
"description_tooltip": null,
|
| 1017 |
+
"layout": "IPY_MODEL_6e2b50925eba416d977a515a96253c8d",
|
| 1018 |
+
"placeholder": "",
|
| 1019 |
+
"style": "IPY_MODEL_66ce6f6abe62413cafc531ddeab1b234",
|
| 1020 |
+
"value": "Downloading (…)solve/main/vocab.txt: 100%"
|
| 1021 |
+
}
|
| 1022 |
+
},
|
| 1023 |
+
"5f331d1562aa4655a7513ebe96e8e543": {
|
| 1024 |
+
"model_module": "@jupyter-widgets/controls",
|
| 1025 |
+
"model_module_version": "1.5.0",
|
| 1026 |
+
"model_name": "HBoxModel",
|
| 1027 |
+
"state": {
|
| 1028 |
+
"_dom_classes": [],
|
| 1029 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 1030 |
+
"_model_module_version": "1.5.0",
|
| 1031 |
+
"_model_name": "HBoxModel",
|
| 1032 |
+
"_view_count": null,
|
| 1033 |
+
"_view_module": "@jupyter-widgets/controls",
|
| 1034 |
+
"_view_module_version": "1.5.0",
|
| 1035 |
+
"_view_name": "HBoxView",
|
| 1036 |
+
"box_style": "",
|
| 1037 |
+
"children": [
|
| 1038 |
+
"IPY_MODEL_5cbc3b58ceb7477aaaf2bb6198f761ae",
|
| 1039 |
+
"IPY_MODEL_a75a8d3737c0495fa94b0d37a7ac7cb2",
|
| 1040 |
+
"IPY_MODEL_fc163ea867554162918e86086bf16346"
|
| 1041 |
+
],
|
| 1042 |
+
"layout": "IPY_MODEL_16e1c6eff9434dccbe888bf31e846cb3"
|
| 1043 |
+
}
|
| 1044 |
+
},
|
| 1045 |
+
"64a97722956b42e78978c674320bffc4": {
|
| 1046 |
+
"model_module": "@jupyter-widgets/controls",
|
| 1047 |
+
"model_module_version": "1.5.0",
|
| 1048 |
+
"model_name": "HBoxModel",
|
| 1049 |
+
"state": {
|
| 1050 |
+
"_dom_classes": [],
|
| 1051 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 1052 |
+
"_model_module_version": "1.5.0",
|
| 1053 |
+
"_model_name": "HBoxModel",
|
| 1054 |
+
"_view_count": null,
|
| 1055 |
+
"_view_module": "@jupyter-widgets/controls",
|
| 1056 |
+
"_view_module_version": "1.5.0",
|
| 1057 |
+
"_view_name": "HBoxView",
|
| 1058 |
+
"box_style": "",
|
| 1059 |
+
"children": [
|
| 1060 |
+
"IPY_MODEL_43c825ca23ee4fa4818012fd0d70e7a0",
|
| 1061 |
+
"IPY_MODEL_e38e3d64e0f94ff28ce00b145aab4b7d",
|
| 1062 |
+
"IPY_MODEL_e70480d3a9d74488b8412057b1c112e7"
|
| 1063 |
+
],
|
| 1064 |
+
"layout": "IPY_MODEL_75f16475449a4af69679a624e7d80b72"
|
| 1065 |
+
}
|
| 1066 |
+
},
|
| 1067 |
+
"66ce6f6abe62413cafc531ddeab1b234": {
|
| 1068 |
+
"model_module": "@jupyter-widgets/controls",
|
| 1069 |
+
"model_module_version": "1.5.0",
|
| 1070 |
+
"model_name": "DescriptionStyleModel",
|
| 1071 |
+
"state": {
|
| 1072 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 1073 |
+
"_model_module_version": "1.5.0",
|
| 1074 |
+
"_model_name": "DescriptionStyleModel",
|
| 1075 |
+
"_view_count": null,
|
| 1076 |
+
"_view_module": "@jupyter-widgets/base",
|
| 1077 |
+
"_view_module_version": "1.2.0",
|
| 1078 |
+
"_view_name": "StyleView",
|
| 1079 |
+
"description_width": ""
|
| 1080 |
+
}
|
| 1081 |
+
},
|
| 1082 |
+
"693f00434dd34f6ebbbd3454e20e6f09": {
|
| 1083 |
+
"model_module": "@jupyter-widgets/controls",
|
| 1084 |
+
"model_module_version": "1.5.0",
|
| 1085 |
+
"model_name": "FloatProgressModel",
|
| 1086 |
+
"state": {
|
| 1087 |
+
"_dom_classes": [],
|
| 1088 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 1089 |
+
"_model_module_version": "1.5.0",
|
| 1090 |
+
"_model_name": "FloatProgressModel",
|
| 1091 |
+
"_view_count": null,
|
| 1092 |
+
"_view_module": "@jupyter-widgets/controls",
|
| 1093 |
+
"_view_module_version": "1.5.0",
|
| 1094 |
+
"_view_name": "ProgressView",
|
| 1095 |
+
"bar_style": "success",
|
| 1096 |
+
"description": "",
|
| 1097 |
+
"description_tooltip": null,
|
| 1098 |
+
"layout": "IPY_MODEL_a1e9be8d15fa48bda098fca408cb1dc3",
|
| 1099 |
+
"max": 59,
|
| 1100 |
+
"min": 0,
|
| 1101 |
+
"orientation": "horizontal",
|
| 1102 |
+
"style": "IPY_MODEL_a6aad0e220554fafabc82b1578ea399b",
|
| 1103 |
+
"value": 59
|
| 1104 |
+
}
|
| 1105 |
+
},
|
| 1106 |
+
"6e2b50925eba416d977a515a96253c8d": {
|
| 1107 |
+
"model_module": "@jupyter-widgets/base",
|
| 1108 |
+
"model_module_version": "1.2.0",
|
| 1109 |
+
"model_name": "LayoutModel",
|
| 1110 |
+
"state": {
|
| 1111 |
+
"_model_module": "@jupyter-widgets/base",
|
| 1112 |
+
"_model_module_version": "1.2.0",
|
| 1113 |
+
"_model_name": "LayoutModel",
|
| 1114 |
+
"_view_count": null,
|
| 1115 |
+
"_view_module": "@jupyter-widgets/base",
|
| 1116 |
+
"_view_module_version": "1.2.0",
|
| 1117 |
+
"_view_name": "LayoutView",
|
| 1118 |
+
"align_content": null,
|
| 1119 |
+
"align_items": null,
|
| 1120 |
+
"align_self": null,
|
| 1121 |
+
"border": null,
|
| 1122 |
+
"bottom": null,
|
| 1123 |
+
"display": null,
|
| 1124 |
+
"flex": null,
|
| 1125 |
+
"flex_flow": null,
|
| 1126 |
+
"grid_area": null,
|
| 1127 |
+
"grid_auto_columns": null,
|
| 1128 |
+
"grid_auto_flow": null,
|
| 1129 |
+
"grid_auto_rows": null,
|
| 1130 |
+
"grid_column": null,
|
| 1131 |
+
"grid_gap": null,
|
| 1132 |
+
"grid_row": null,
|
| 1133 |
+
"grid_template_areas": null,
|
| 1134 |
+
"grid_template_columns": null,
|
| 1135 |
+
"grid_template_rows": null,
|
| 1136 |
+
"height": null,
|
| 1137 |
+
"justify_content": null,
|
| 1138 |
+
"justify_items": null,
|
| 1139 |
+
"left": null,
|
| 1140 |
+
"margin": null,
|
| 1141 |
+
"max_height": null,
|
| 1142 |
+
"max_width": null,
|
| 1143 |
+
"min_height": null,
|
| 1144 |
+
"min_width": null,
|
| 1145 |
+
"object_fit": null,
|
| 1146 |
+
"object_position": null,
|
| 1147 |
+
"order": null,
|
| 1148 |
+
"overflow": null,
|
| 1149 |
+
"overflow_x": null,
|
| 1150 |
+
"overflow_y": null,
|
| 1151 |
+
"padding": null,
|
| 1152 |
+
"right": null,
|
| 1153 |
+
"top": null,
|
| 1154 |
+
"visibility": null,
|
| 1155 |
+
"width": null
|
| 1156 |
+
}
|
| 1157 |
+
},
|
| 1158 |
+
"6f6bb49fc5cb49b2b61d5da84a85df48": {
|
| 1159 |
+
"model_module": "@jupyter-widgets/controls",
|
| 1160 |
+
"model_module_version": "1.5.0",
|
| 1161 |
+
"model_name": "HTMLModel",
|
| 1162 |
+
"state": {
|
| 1163 |
+
"_dom_classes": [],
|
| 1164 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 1165 |
+
"_model_module_version": "1.5.0",
|
| 1166 |
+
"_model_name": "HTMLModel",
|
| 1167 |
+
"_view_count": null,
|
| 1168 |
+
"_view_module": "@jupyter-widgets/controls",
|
| 1169 |
+
"_view_module_version": "1.5.0",
|
| 1170 |
+
"_view_name": "HTMLView",
|
| 1171 |
+
"description": "",
|
| 1172 |
+
"description_tooltip": null,
|
| 1173 |
+
"layout": "IPY_MODEL_44b676a38c90434c92230d740d8d953b",
|
| 1174 |
+
"placeholder": "",
|
| 1175 |
+
"style": "IPY_MODEL_00a05a5b259d4e9d8219d18f1b6fd9fe",
|
| 1176 |
+
"value": "Downloading (…)okenizer_config.json: 100%"
|
| 1177 |
+
}
|
| 1178 |
+
},
|
| 1179 |
+
"75f16475449a4af69679a624e7d80b72": {
|
| 1180 |
+
"model_module": "@jupyter-widgets/base",
|
| 1181 |
+
"model_module_version": "1.2.0",
|
| 1182 |
+
"model_name": "LayoutModel",
|
| 1183 |
+
"state": {
|
| 1184 |
+
"_model_module": "@jupyter-widgets/base",
|
| 1185 |
+
"_model_module_version": "1.2.0",
|
| 1186 |
+
"_model_name": "LayoutModel",
|
| 1187 |
+
"_view_count": null,
|
| 1188 |
+
"_view_module": "@jupyter-widgets/base",
|
| 1189 |
+
"_view_module_version": "1.2.0",
|
| 1190 |
+
"_view_name": "LayoutView",
|
| 1191 |
+
"align_content": null,
|
| 1192 |
+
"align_items": null,
|
| 1193 |
+
"align_self": null,
|
| 1194 |
+
"border": null,
|
| 1195 |
+
"bottom": null,
|
| 1196 |
+
"display": null,
|
| 1197 |
+
"flex": null,
|
| 1198 |
+
"flex_flow": null,
|
| 1199 |
+
"grid_area": null,
|
| 1200 |
+
"grid_auto_columns": null,
|
| 1201 |
+
"grid_auto_flow": null,
|
| 1202 |
+
"grid_auto_rows": null,
|
| 1203 |
+
"grid_column": null,
|
| 1204 |
+
"grid_gap": null,
|
| 1205 |
+
"grid_row": null,
|
| 1206 |
+
"grid_template_areas": null,
|
| 1207 |
+
"grid_template_columns": null,
|
| 1208 |
+
"grid_template_rows": null,
|
| 1209 |
+
"height": null,
|
| 1210 |
+
"justify_content": null,
|
| 1211 |
+
"justify_items": null,
|
| 1212 |
+
"left": null,
|
| 1213 |
+
"margin": null,
|
| 1214 |
+
"max_height": null,
|
| 1215 |
+
"max_width": null,
|
| 1216 |
+
"min_height": null,
|
| 1217 |
+
"min_width": null,
|
| 1218 |
+
"object_fit": null,
|
| 1219 |
+
"object_position": null,
|
| 1220 |
+
"order": null,
|
| 1221 |
+
"overflow": null,
|
| 1222 |
+
"overflow_x": null,
|
| 1223 |
+
"overflow_y": null,
|
| 1224 |
+
"padding": null,
|
| 1225 |
+
"right": null,
|
| 1226 |
+
"top": null,
|
| 1227 |
+
"visibility": null,
|
| 1228 |
+
"width": null
|
| 1229 |
+
}
|
| 1230 |
+
},
|
| 1231 |
+
"90d1288635e84948b23e428c59c140e8": {
|
| 1232 |
+
"model_module": "@jupyter-widgets/base",
|
| 1233 |
+
"model_module_version": "1.2.0",
|
| 1234 |
+
"model_name": "LayoutModel",
|
| 1235 |
+
"state": {
|
| 1236 |
+
"_model_module": "@jupyter-widgets/base",
|
| 1237 |
+
"_model_module_version": "1.2.0",
|
| 1238 |
+
"_model_name": "LayoutModel",
|
| 1239 |
+
"_view_count": null,
|
| 1240 |
+
"_view_module": "@jupyter-widgets/base",
|
| 1241 |
+
"_view_module_version": "1.2.0",
|
| 1242 |
+
"_view_name": "LayoutView",
|
| 1243 |
+
"align_content": null,
|
| 1244 |
+
"align_items": null,
|
| 1245 |
+
"align_self": null,
|
| 1246 |
+
"border": null,
|
| 1247 |
+
"bottom": null,
|
| 1248 |
+
"display": null,
|
| 1249 |
+
"flex": null,
|
| 1250 |
+
"flex_flow": null,
|
| 1251 |
+
"grid_area": null,
|
| 1252 |
+
"grid_auto_columns": null,
|
| 1253 |
+
"grid_auto_flow": null,
|
| 1254 |
+
"grid_auto_rows": null,
|
| 1255 |
+
"grid_column": null,
|
| 1256 |
+
"grid_gap": null,
|
| 1257 |
+
"grid_row": null,
|
| 1258 |
+
"grid_template_areas": null,
|
| 1259 |
+
"grid_template_columns": null,
|
| 1260 |
+
"grid_template_rows": null,
|
| 1261 |
+
"height": null,
|
| 1262 |
+
"justify_content": null,
|
| 1263 |
+
"justify_items": null,
|
| 1264 |
+
"left": null,
|
| 1265 |
+
"margin": null,
|
| 1266 |
+
"max_height": null,
|
| 1267 |
+
"max_width": null,
|
| 1268 |
+
"min_height": null,
|
| 1269 |
+
"min_width": null,
|
| 1270 |
+
"object_fit": null,
|
| 1271 |
+
"object_position": null,
|
| 1272 |
+
"order": null,
|
| 1273 |
+
"overflow": null,
|
| 1274 |
+
"overflow_x": null,
|
| 1275 |
+
"overflow_y": null,
|
| 1276 |
+
"padding": null,
|
| 1277 |
+
"right": null,
|
| 1278 |
+
"top": null,
|
| 1279 |
+
"visibility": null,
|
| 1280 |
+
"width": null
|
| 1281 |
+
}
|
| 1282 |
+
},
|
| 1283 |
+
"a1e9be8d15fa48bda098fca408cb1dc3": {
|
| 1284 |
+
"model_module": "@jupyter-widgets/base",
|
| 1285 |
+
"model_module_version": "1.2.0",
|
| 1286 |
+
"model_name": "LayoutModel",
|
| 1287 |
+
"state": {
|
| 1288 |
+
"_model_module": "@jupyter-widgets/base",
|
| 1289 |
+
"_model_module_version": "1.2.0",
|
| 1290 |
+
"_model_name": "LayoutModel",
|
| 1291 |
+
"_view_count": null,
|
| 1292 |
+
"_view_module": "@jupyter-widgets/base",
|
| 1293 |
+
"_view_module_version": "1.2.0",
|
| 1294 |
+
"_view_name": "LayoutView",
|
| 1295 |
+
"align_content": null,
|
| 1296 |
+
"align_items": null,
|
| 1297 |
+
"align_self": null,
|
| 1298 |
+
"border": null,
|
| 1299 |
+
"bottom": null,
|
| 1300 |
+
"display": null,
|
| 1301 |
+
"flex": null,
|
| 1302 |
+
"flex_flow": null,
|
| 1303 |
+
"grid_area": null,
|
| 1304 |
+
"grid_auto_columns": null,
|
| 1305 |
+
"grid_auto_flow": null,
|
| 1306 |
+
"grid_auto_rows": null,
|
| 1307 |
+
"grid_column": null,
|
| 1308 |
+
"grid_gap": null,
|
| 1309 |
+
"grid_row": null,
|
| 1310 |
+
"grid_template_areas": null,
|
| 1311 |
+
"grid_template_columns": null,
|
| 1312 |
+
"grid_template_rows": null,
|
| 1313 |
+
"height": null,
|
| 1314 |
+
"justify_content": null,
|
| 1315 |
+
"justify_items": null,
|
| 1316 |
+
"left": null,
|
| 1317 |
+
"margin": null,
|
| 1318 |
+
"max_height": null,
|
| 1319 |
+
"max_width": null,
|
| 1320 |
+
"min_height": null,
|
| 1321 |
+
"min_width": null,
|
| 1322 |
+
"object_fit": null,
|
| 1323 |
+
"object_position": null,
|
| 1324 |
+
"order": null,
|
| 1325 |
+
"overflow": null,
|
| 1326 |
+
"overflow_x": null,
|
| 1327 |
+
"overflow_y": null,
|
| 1328 |
+
"padding": null,
|
| 1329 |
+
"right": null,
|
| 1330 |
+
"top": null,
|
| 1331 |
+
"visibility": null,
|
| 1332 |
+
"width": null
|
| 1333 |
+
}
|
| 1334 |
+
},
|
| 1335 |
+
"a6aad0e220554fafabc82b1578ea399b": {
|
| 1336 |
+
"model_module": "@jupyter-widgets/controls",
|
| 1337 |
+
"model_module_version": "1.5.0",
|
| 1338 |
+
"model_name": "ProgressStyleModel",
|
| 1339 |
+
"state": {
|
| 1340 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 1341 |
+
"_model_module_version": "1.5.0",
|
| 1342 |
+
"_model_name": "ProgressStyleModel",
|
| 1343 |
+
"_view_count": null,
|
| 1344 |
+
"_view_module": "@jupyter-widgets/base",
|
| 1345 |
+
"_view_module_version": "1.2.0",
|
| 1346 |
+
"_view_name": "StyleView",
|
| 1347 |
+
"bar_color": null,
|
| 1348 |
+
"description_width": ""
|
| 1349 |
+
}
|
| 1350 |
+
},
|
| 1351 |
+
"a75a8d3737c0495fa94b0d37a7ac7cb2": {
|
| 1352 |
+
"model_module": "@jupyter-widgets/controls",
|
| 1353 |
+
"model_module_version": "1.5.0",
|
| 1354 |
+
"model_name": "FloatProgressModel",
|
| 1355 |
+
"state": {
|
| 1356 |
+
"_dom_classes": [],
|
| 1357 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 1358 |
+
"_model_module_version": "1.5.0",
|
| 1359 |
+
"_model_name": "FloatProgressModel",
|
| 1360 |
+
"_view_count": null,
|
| 1361 |
+
"_view_module": "@jupyter-widgets/controls",
|
| 1362 |
+
"_view_module_version": "1.5.0",
|
| 1363 |
+
"_view_name": "ProgressView",
|
| 1364 |
+
"bar_style": "success",
|
| 1365 |
+
"description": "",
|
| 1366 |
+
"description_tooltip": null,
|
| 1367 |
+
"layout": "IPY_MODEL_4c444591789a439ea012c19b9a65943c",
|
| 1368 |
+
"max": 1233088,
|
| 1369 |
+
"min": 0,
|
| 1370 |
+
"orientation": "horizontal",
|
| 1371 |
+
"style": "IPY_MODEL_e95963b069c0430493068fccad39e549",
|
| 1372 |
+
"value": 1233088
|
| 1373 |
+
}
|
| 1374 |
+
},
|
| 1375 |
+
"a89f2e52c5ab4210915eec5bb8a67162": {
|
| 1376 |
+
"model_module": "@jupyter-widgets/controls",
|
| 1377 |
+
"model_module_version": "1.5.0",
|
| 1378 |
+
"model_name": "ProgressStyleModel",
|
| 1379 |
+
"state": {
|
| 1380 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 1381 |
+
"_model_module_version": "1.5.0",
|
| 1382 |
+
"_model_name": "ProgressStyleModel",
|
| 1383 |
+
"_view_count": null,
|
| 1384 |
+
"_view_module": "@jupyter-widgets/base",
|
| 1385 |
+
"_view_module_version": "1.2.0",
|
| 1386 |
+
"_view_name": "StyleView",
|
| 1387 |
+
"bar_color": null,
|
| 1388 |
+
"description_width": ""
|
| 1389 |
+
}
|
| 1390 |
+
},
|
| 1391 |
+
"b4eb927b4c0143cab3346d4521245103": {
|
| 1392 |
+
"model_module": "@jupyter-widgets/base",
|
| 1393 |
+
"model_module_version": "1.2.0",
|
| 1394 |
+
"model_name": "LayoutModel",
|
| 1395 |
+
"state": {
|
| 1396 |
+
"_model_module": "@jupyter-widgets/base",
|
| 1397 |
+
"_model_module_version": "1.2.0",
|
| 1398 |
+
"_model_name": "LayoutModel",
|
| 1399 |
+
"_view_count": null,
|
| 1400 |
+
"_view_module": "@jupyter-widgets/base",
|
| 1401 |
+
"_view_module_version": "1.2.0",
|
| 1402 |
+
"_view_name": "LayoutView",
|
| 1403 |
+
"align_content": null,
|
| 1404 |
+
"align_items": null,
|
| 1405 |
+
"align_self": null,
|
| 1406 |
+
"border": null,
|
| 1407 |
+
"bottom": null,
|
| 1408 |
+
"display": null,
|
| 1409 |
+
"flex": null,
|
| 1410 |
+
"flex_flow": null,
|
| 1411 |
+
"grid_area": null,
|
| 1412 |
+
"grid_auto_columns": null,
|
| 1413 |
+
"grid_auto_flow": null,
|
| 1414 |
+
"grid_auto_rows": null,
|
| 1415 |
+
"grid_column": null,
|
| 1416 |
+
"grid_gap": null,
|
| 1417 |
+
"grid_row": null,
|
| 1418 |
+
"grid_template_areas": null,
|
| 1419 |
+
"grid_template_columns": null,
|
| 1420 |
+
"grid_template_rows": null,
|
| 1421 |
+
"height": null,
|
| 1422 |
+
"justify_content": null,
|
| 1423 |
+
"justify_items": null,
|
| 1424 |
+
"left": null,
|
| 1425 |
+
"margin": null,
|
| 1426 |
+
"max_height": null,
|
| 1427 |
+
"max_width": null,
|
| 1428 |
+
"min_height": null,
|
| 1429 |
+
"min_width": null,
|
| 1430 |
+
"object_fit": null,
|
| 1431 |
+
"object_position": null,
|
| 1432 |
+
"order": null,
|
| 1433 |
+
"overflow": null,
|
| 1434 |
+
"overflow_x": null,
|
| 1435 |
+
"overflow_y": null,
|
| 1436 |
+
"padding": null,
|
| 1437 |
+
"right": null,
|
| 1438 |
+
"top": null,
|
| 1439 |
+
"visibility": null,
|
| 1440 |
+
"width": null
|
| 1441 |
+
}
|
| 1442 |
+
},
|
| 1443 |
+
"c4325e65d0b04cc0bce40f6f4a273eb2": {
|
| 1444 |
+
"model_module": "@jupyter-widgets/controls",
|
| 1445 |
+
"model_module_version": "1.5.0",
|
| 1446 |
+
"model_name": "DescriptionStyleModel",
|
| 1447 |
+
"state": {
|
| 1448 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 1449 |
+
"_model_module_version": "1.5.0",
|
| 1450 |
+
"_model_name": "DescriptionStyleModel",
|
| 1451 |
+
"_view_count": null,
|
| 1452 |
+
"_view_module": "@jupyter-widgets/base",
|
| 1453 |
+
"_view_module_version": "1.2.0",
|
| 1454 |
+
"_view_name": "StyleView",
|
| 1455 |
+
"description_width": ""
|
| 1456 |
+
}
|
| 1457 |
+
},
|
| 1458 |
+
"e38e3d64e0f94ff28ce00b145aab4b7d": {
|
| 1459 |
+
"model_module": "@jupyter-widgets/controls",
|
| 1460 |
+
"model_module_version": "1.5.0",
|
| 1461 |
+
"model_name": "FloatProgressModel",
|
| 1462 |
+
"state": {
|
| 1463 |
+
"_dom_classes": [],
|
| 1464 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 1465 |
+
"_model_module_version": "1.5.0",
|
| 1466 |
+
"_model_name": "FloatProgressModel",
|
| 1467 |
+
"_view_count": null,
|
| 1468 |
+
"_view_module": "@jupyter-widgets/controls",
|
| 1469 |
+
"_view_module_version": "1.5.0",
|
| 1470 |
+
"_view_name": "ProgressView",
|
| 1471 |
+
"bar_style": "success",
|
| 1472 |
+
"description": "",
|
| 1473 |
+
"description_tooltip": null,
|
| 1474 |
+
"layout": "IPY_MODEL_90d1288635e84948b23e428c59c140e8",
|
| 1475 |
+
"max": 386,
|
| 1476 |
+
"min": 0,
|
| 1477 |
+
"orientation": "horizontal",
|
| 1478 |
+
"style": "IPY_MODEL_a89f2e52c5ab4210915eec5bb8a67162",
|
| 1479 |
+
"value": 386
|
| 1480 |
+
}
|
| 1481 |
+
},
|
| 1482 |
+
"e70480d3a9d74488b8412057b1c112e7": {
|
| 1483 |
+
"model_module": "@jupyter-widgets/controls",
|
| 1484 |
+
"model_module_version": "1.5.0",
|
| 1485 |
+
"model_name": "HTMLModel",
|
| 1486 |
+
"state": {
|
| 1487 |
+
"_dom_classes": [],
|
| 1488 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 1489 |
+
"_model_module_version": "1.5.0",
|
| 1490 |
+
"_model_name": "HTMLModel",
|
| 1491 |
+
"_view_count": null,
|
| 1492 |
+
"_view_module": "@jupyter-widgets/controls",
|
| 1493 |
+
"_view_module_version": "1.5.0",
|
| 1494 |
+
"_view_name": "HTMLView",
|
| 1495 |
+
"description": "",
|
| 1496 |
+
"description_tooltip": null,
|
| 1497 |
+
"layout": "IPY_MODEL_fd086c70086d445b9152c65db68ffa40",
|
| 1498 |
+
"placeholder": "",
|
| 1499 |
+
"style": "IPY_MODEL_3c18c7c120c2428595d75cd10bc59ad4",
|
| 1500 |
+
"value": " 386/386 [00:00<00:00, 17.3kB/s]"
|
| 1501 |
+
}
|
| 1502 |
+
},
|
| 1503 |
+
"e95963b069c0430493068fccad39e549": {
|
| 1504 |
+
"model_module": "@jupyter-widgets/controls",
|
| 1505 |
+
"model_module_version": "1.5.0",
|
| 1506 |
+
"model_name": "ProgressStyleModel",
|
| 1507 |
+
"state": {
|
| 1508 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 1509 |
+
"_model_module_version": "1.5.0",
|
| 1510 |
+
"_model_name": "ProgressStyleModel",
|
| 1511 |
+
"_view_count": null,
|
| 1512 |
+
"_view_module": "@jupyter-widgets/base",
|
| 1513 |
+
"_view_module_version": "1.2.0",
|
| 1514 |
+
"_view_name": "StyleView",
|
| 1515 |
+
"bar_color": null,
|
| 1516 |
+
"description_width": ""
|
| 1517 |
+
}
|
| 1518 |
+
},
|
| 1519 |
+
"f36aadfead2f4ea5bffc5380d1389f83": {
|
| 1520 |
+
"model_module": "@jupyter-widgets/controls",
|
| 1521 |
+
"model_module_version": "1.5.0",
|
| 1522 |
+
"model_name": "DescriptionStyleModel",
|
| 1523 |
+
"state": {
|
| 1524 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 1525 |
+
"_model_module_version": "1.5.0",
|
| 1526 |
+
"_model_name": "DescriptionStyleModel",
|
| 1527 |
+
"_view_count": null,
|
| 1528 |
+
"_view_module": "@jupyter-widgets/base",
|
| 1529 |
+
"_view_module_version": "1.2.0",
|
| 1530 |
+
"_view_name": "StyleView",
|
| 1531 |
+
"description_width": ""
|
| 1532 |
+
}
|
| 1533 |
+
},
|
| 1534 |
+
"f7dcb80ead674ea2acca13be918cf29f": {
|
| 1535 |
+
"model_module": "@jupyter-widgets/controls",
|
| 1536 |
+
"model_module_version": "1.5.0",
|
| 1537 |
+
"model_name": "HBoxModel",
|
| 1538 |
+
"state": {
|
| 1539 |
+
"_dom_classes": [],
|
| 1540 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 1541 |
+
"_model_module_version": "1.5.0",
|
| 1542 |
+
"_model_name": "HBoxModel",
|
| 1543 |
+
"_view_count": null,
|
| 1544 |
+
"_view_module": "@jupyter-widgets/controls",
|
| 1545 |
+
"_view_module_version": "1.5.0",
|
| 1546 |
+
"_view_name": "HBoxView",
|
| 1547 |
+
"box_style": "",
|
| 1548 |
+
"children": [
|
| 1549 |
+
"IPY_MODEL_6f6bb49fc5cb49b2b61d5da84a85df48",
|
| 1550 |
+
"IPY_MODEL_693f00434dd34f6ebbbd3454e20e6f09",
|
| 1551 |
+
"IPY_MODEL_182030415ce843bfb55c450688f1173c"
|
| 1552 |
+
],
|
| 1553 |
+
"layout": "IPY_MODEL_26489266a0af48769920239061ea348c"
|
| 1554 |
+
}
|
| 1555 |
+
},
|
| 1556 |
+
"fb886858d4ad4ac0a1d9e8e56941b246": {
|
| 1557 |
+
"model_module": "@jupyter-widgets/controls",
|
| 1558 |
+
"model_module_version": "1.5.0",
|
| 1559 |
+
"model_name": "DescriptionStyleModel",
|
| 1560 |
+
"state": {
|
| 1561 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 1562 |
+
"_model_module_version": "1.5.0",
|
| 1563 |
+
"_model_name": "DescriptionStyleModel",
|
| 1564 |
+
"_view_count": null,
|
| 1565 |
+
"_view_module": "@jupyter-widgets/base",
|
| 1566 |
+
"_view_module_version": "1.2.0",
|
| 1567 |
+
"_view_name": "StyleView",
|
| 1568 |
+
"description_width": ""
|
| 1569 |
+
}
|
| 1570 |
+
},
|
| 1571 |
+
"fc163ea867554162918e86086bf16346": {
|
| 1572 |
+
"model_module": "@jupyter-widgets/controls",
|
| 1573 |
+
"model_module_version": "1.5.0",
|
| 1574 |
+
"model_name": "HTMLModel",
|
| 1575 |
+
"state": {
|
| 1576 |
+
"_dom_classes": [],
|
| 1577 |
+
"_model_module": "@jupyter-widgets/controls",
|
| 1578 |
+
"_model_module_version": "1.5.0",
|
| 1579 |
+
"_model_name": "HTMLModel",
|
| 1580 |
+
"_view_count": null,
|
| 1581 |
+
"_view_module": "@jupyter-widgets/controls",
|
| 1582 |
+
"_view_module_version": "1.5.0",
|
| 1583 |
+
"_view_name": "HTMLView",
|
| 1584 |
+
"description": "",
|
| 1585 |
+
"description_tooltip": null,
|
| 1586 |
+
"layout": "IPY_MODEL_05ba2899712c41dfbe19b47e310d6f11",
|
| 1587 |
+
"placeholder": "",
|
| 1588 |
+
"style": "IPY_MODEL_f36aadfead2f4ea5bffc5380d1389f83",
|
| 1589 |
+
"value": " 1.23M/1.23M [00:00<00:00, 6.07MB/s]"
|
| 1590 |
+
}
|
| 1591 |
+
},
|
| 1592 |
+
"fd086c70086d445b9152c65db68ffa40": {
|
| 1593 |
+
"model_module": "@jupyter-widgets/base",
|
| 1594 |
+
"model_module_version": "1.2.0",
|
| 1595 |
+
"model_name": "LayoutModel",
|
| 1596 |
+
"state": {
|
| 1597 |
+
"_model_module": "@jupyter-widgets/base",
|
| 1598 |
+
"_model_module_version": "1.2.0",
|
| 1599 |
+
"_model_name": "LayoutModel",
|
| 1600 |
+
"_view_count": null,
|
| 1601 |
+
"_view_module": "@jupyter-widgets/base",
|
| 1602 |
+
"_view_module_version": "1.2.0",
|
| 1603 |
+
"_view_name": "LayoutView",
|
| 1604 |
+
"align_content": null,
|
| 1605 |
+
"align_items": null,
|
| 1606 |
+
"align_self": null,
|
| 1607 |
+
"border": null,
|
| 1608 |
+
"bottom": null,
|
| 1609 |
+
"display": null,
|
| 1610 |
+
"flex": null,
|
| 1611 |
+
"flex_flow": null,
|
| 1612 |
+
"grid_area": null,
|
| 1613 |
+
"grid_auto_columns": null,
|
| 1614 |
+
"grid_auto_flow": null,
|
| 1615 |
+
"grid_auto_rows": null,
|
| 1616 |
+
"grid_column": null,
|
| 1617 |
+
"grid_gap": null,
|
| 1618 |
+
"grid_row": null,
|
| 1619 |
+
"grid_template_areas": null,
|
| 1620 |
+
"grid_template_columns": null,
|
| 1621 |
+
"grid_template_rows": null,
|
| 1622 |
+
"height": null,
|
| 1623 |
+
"justify_content": null,
|
| 1624 |
+
"justify_items": null,
|
| 1625 |
+
"left": null,
|
| 1626 |
+
"margin": null,
|
| 1627 |
+
"max_height": null,
|
| 1628 |
+
"max_width": null,
|
| 1629 |
+
"min_height": null,
|
| 1630 |
+
"min_width": null,
|
| 1631 |
+
"object_fit": null,
|
| 1632 |
+
"object_position": null,
|
| 1633 |
+
"order": null,
|
| 1634 |
+
"overflow": null,
|
| 1635 |
+
"overflow_x": null,
|
| 1636 |
+
"overflow_y": null,
|
| 1637 |
+
"padding": null,
|
| 1638 |
+
"right": null,
|
| 1639 |
+
"top": null,
|
| 1640 |
+
"visibility": null,
|
| 1641 |
+
"width": null
|
| 1642 |
+
}
|
| 1643 |
+
}
|
| 1644 |
+
}
|
| 1645 |
+
}
|
| 1646 |
+
},
|
| 1647 |
+
"nbformat": 4,
|
| 1648 |
+
"nbformat_minor": 1
|
| 1649 |
+
}
|
sontotalmodel_finallll.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:36d76675d23a73c621367fd7640ff3187b1fc0221e3e06a8b53306410077c953
|
| 3 |
+
size 739838472
|