Update params.py (#31)

Author: prakashpandey9

README.md

@@ -1,7 +1,7 @@
 # R-NET: MACHINE READING COMPREHENSION WITH SELF MATCHING NETWORKS
 
 Tensorflow implementation of https://www.microsoft.com/en-us/research/wp-content/uploads/2017/05/r-net.pdf
-![Alt text](/../demo/screenshots/demo.gif?)
+![Alt text](/../dev/screenshots/architecture.png?raw=true "R-NET")
 
 The dataset used for this task is Stanford Question Answering Dataset (https://rajpurkar.github.io/SQuAD-explorer/). Pretrained GloVe embeddings are used for both words (https://nlp.stanford.edu/projects/glove/) and characters (https://github.com/minimaxir/char-embeddings/blob/master/glove.840B.300d-char.txt).
 

params.py

@@ -40,7 +40,7 @@ class Params():
     max_p_len = 300 # Maximum number of words in each passage context
     max_q_len = 30 # Maximum number of words in each question context
     max_char_len = 16 # Maximum number of characters in a word
-    vocab_size = 91604 # Number of vocabs in glove.840B.300d.txt + 1 for an unknown token
+    vocab_size = 91605 # Number of vocabs in glove.840B.300d.txt + 1 for an unknown token
     char_vocab_size = 95 # Number of characters in glove.840B.300d.char.txt + 1 for an unknown character
     emb_size = 300 # Embeddings size for words
     char_emb_size = 8 # Embeddings size for characters