update from_pretrained to load XLNetModel as well

examples/generation_xlnet.py

@@ -0,0 +1,21 @@
+import torch
+from torch.nn import functional as F
+from pytorch_pretrained_bert import XLNetModel, XLNetLMHeadModel, XLNetTokenizer
+
+import logging
+logging.basicConfig(level=logging.INFO)
+
+tokenizer = XLNetTokenizer.from_pretrained('xlnet-large-cased')
+model = XLNetModel.from_pretrained('xlnet-large-cased')
+model = XLNetLMHeadModel.from_pretrained('xlnet-large-cased')
+
+tokens = tokenizer.encode('I am very ')
+for i in range(len(tokens), 20):
+    mask = torch.tensor([[[0.0] * i + [1.0]]])
+    logits, _ = model(torch.tensor([tokens + [0]]),
+                      perm_mask=mask.expand(-1, i+1, -1),
+                      target_mapping=mask,
+                      inp_q=mask.squeeze(1))
+    output = torch.multinomial(F.softmax(logits[0, 0, :]), 1)
+    tokens.append(output.item())
+    print(tokenizer.decode(tokens))