fix: initialize LoRA params on same device as wrapped linear

apply_lora() is called after generator.to(device), so lora_A/lora_B were
being created on CPU while the rest of the model was on CUDA.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

selva_core/model/lora.py

@@ -42,8 +42,9 @@ class LoRALinear(nn.Module):
             linear.bias.requires_grad_(False)
 
         ref_dtype   = linear.weight.dtype
-        self.lora_A = nn.Parameter(torch.empty(rank, in_f, dtype=ref_dtype))
-        self.lora_B = nn.Parameter(torch.zeros(out_f, rank, dtype=ref_dtype))
+        ref_device  = linear.weight.device
+        self.lora_A = nn.Parameter(torch.empty(rank, in_f, dtype=ref_dtype, device=ref_device))
+        self.lora_B = nn.Parameter(torch.zeros(out_f, rank, dtype=ref_dtype, device=ref_device))
         self.scale  = alpha / rank
 
         nn.init.kaiming_uniform_(self.lora_A, a=math.sqrt(5))