from keras.layers.core import Dense, Activation
from keras.layers import Flatten, Dropout
from keras.layers.embeddings import Embedding
from keras.models import Sequential

embedding_layer = Embedding(embedding_weights.shape[0],
 embedding_weights.shape[1],
 weights=[embedding_weights],
 input_length=max_length)

model = Sequential()
model.add(embedding_layer)
model.add(Flatten())
model.add(Dense(128, activation='linear'))
model.add(Dropout(0.5)) 
model.add(Dense(1))
model.add(Activation('linear'))
model.compile(loss='mean_absolute_error', optimizer='sgd',metrics=['mae'])