Remove single ]

app.py

@@ -136,7 +136,7 @@ def generate_diffusion_text(input_ids):
         input_tensor = torch.tensor([input_ids], dtype=torch.long).to(model.device)
         logits = model(input_ids=input_tensor)["logits"]
         probs = torch.nn.functional.softmax(logits, dim=-1)[0]
-        probs = torch.clamp(probs, min=1e-8, max=1.0)]
+        probs = torch.clamp(probs, min=1e-8, max=1.0)
         print("probs", probs)
         print("probs min:", probs.min().item(), "max:", probs.max().item(), "sum:", probs.sum().item())
         assert torch.all(torch.isfinite(probs)), "Non-finite values in probs!"