Update Text-Generation.py

Text-Generation.py

@@ -88,10 +88,10 @@ def get_next_word_without_e(input_sequence):
     if temperature != 1.0:
         next_token_candidates_logits = next_token_candidates_logits / temperature
     # filter
-    filtered_next_token_candidates_logits = top_k_top_p_filtering(next_token_candidates_logits, top_k=number_of_tokens_to_sample, top_p=number_of_tokens_to_sample)
+    filtered_next_token_candidates_logits = top_k_top_p_filtering(next_token_candidates_logits, top_k=int(number_of_tokens_to_sample), top_p=int(number_of_tokens_to_sample))
     # sample and get a probability distribution
     probs = F.softmax(filtered_next_token_candidates_logits, dim=-1)
-    next_token_candidates = torch.multinomial(probs, num_samples=number_of_tokens_to_sample) ## 10000 random samples
+    next_token_candidates = torch.multinomial(probs, num_samples=int(number_of_tokens_to_sample)) ## 10000 random samples
     word_list = []
     for candidate_string in next_token_candidates:
         for candidate in candidate_string: