diff --git a/LanguageModel.lua b/LanguageModel.lua
index d6248184..70b2f9d1 100644
--- a/LanguageModel.lua
+++ b/LanguageModel.lua
@@ -132,16 +132,8 @@ function LM:encode_string(s)
   return encoded
 end
 
-
-function LM:decode_string(encoded)
-  assert(torch.isTensor(encoded) and encoded:dim() == 1)
-  local s = ''
-  for i = 1, encoded:size(1) do
-    local idx = encoded[i]
-    local token = self.idx_to_token[idx]
-    s = s .. token
-  end
-  return s
+function LM:decode_char(encoded)
+  return self.idx_to_token[encoded[1][1]]
 end
 
 
@@ -162,8 +154,8 @@ function LM:sample(kwargs)
   local verbose = utils.get_kwarg(kwargs, 'verbose', 0)
   local sample = utils.get_kwarg(kwargs, 'sample', 1)
   local temperature = utils.get_kwarg(kwargs, 'temperature', 1)
+  local write = io.write
 
-  local sampled = torch.LongTensor(1, T)
   self:resetStates()
 
   local scores, first_t
@@ -173,7 +165,7 @@ function LM:sample(kwargs)
     end
     local x = self:encode_string(start_text):view(1, -1)
     local T0 = x:size(2)
-    sampled[{{}, {1, T0}}]:copy(x)
+    write(start_text)
     scores = self:forward(x)[{{}, {T0, T0}}]
     first_t = T0 + 1
   else
@@ -195,12 +187,12 @@ function LM:sample(kwargs)
        probs:div(torch.sum(probs))
        next_char = torch.multinomial(probs, 1):view(1, 1)
     end
-    sampled[{{}, {t, t}}]:copy(next_char)
+    write(self:decode_char(next_char))
     scores = self:forward(next_char)
   end
 
   self:resetStates()
-  return self:decode_string(sampled[1])
+  write('\n')
 end
 
 
diff --git a/sample.lua b/sample.lua
index 4e6ebae0..2e7548a0 100644
--- a/sample.lua
+++ b/sample.lua
@@ -38,5 +38,4 @@ if opt.verbose == 1 then print(msg) end
 
 model:evaluate()
 
-local sample = model:sample(opt)
-print(sample)
+model:sample(opt)