added float numbers as result

app.py

@@ -37,9 +37,7 @@ def weightsbias(weight,bias,predicted,progress=gr.Progress()):
     t = torch.tensor([predicted],dtype=torch.float32)
     rout = model(t)
     c = model.state_dict()
-    def ceil(x):
-        return math.ceil(x)
-    return [ceil(rout.item()),ceil(c['l.weight'].item()),ceil(c['l.bias'].item())]
+    return [rout.item(),c['l.weight'].item(),c['l.bias'].item()]
 
 
 with gr.Blocks() as iface: