Update app.py

app.py

@@ -1,8 +1,47 @@
-from transformers import AutoModel, AutoTokenizer 
+import streamlit as st
 
-model_name = "ml6team/gpt-2-small-conditional-quote-generator" 
-model = AutoModel.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
+import tensorflow as tf
+config = tf.compat.v1.ConfigProto(intra_op_parallelism_threads=3, 
+                        inter_op_parallelism_threads=2, 
+                        allow_soft_placement=True,
+                        device_count = {'GPU':1, 'CPU':4})
 
-inputs = tokenizer("Hello world!", return_tensors="pt")
-outputs = model(**inputs)
+session = tf.compat.v1.Session(config=config)
+
+#for reproducability
+SEED = 64
+
+#maximum number of words in output text
+# MAX_LEN = 30
+
+title = st.text_input('Enter the seed words', ' ')
+input_sequence = title
+
+number = st.number_input('Insert how many words', 1)
+MAX_LEN = number
+
+if st.button('Submit'):
+
+    #get transformers
+    from transformers import TFGPT2LMHeadModel, GPT2Tokenizer
+
+    tokenizer = GPT2Tokenizer.from_pretrained("gpt-2")
+    GPT2 = TFGPT2LMHeadModel.from_pretrained("gpt-2", pad_token_id=tokenizer.eos_token_id)
+
+    import tensorflow as tf
+    tf.random.set_seed(SEED)
+    input_ids = tokenizer.encode(input_sequence, return_tensors='tf')
+
+    input_ids = tokenizer.encode(input_sequence, return_tensors='tf')
+
+# generate text until the output length (which includes the context length) reaches 50
+    greedy_output = GPT2.generate(input_ids, max_length = MAX_LEN)
+
+    print("Output:\n" + 100 * '-')
+    print(tokenizer.decode(greedy_output[0], skip_special_tokens = True))
+else:
+    st.write(' ')
+
+
+# print("Output:\n" + 100 * '-')
+# print(tokenizer.decode(sample_output[0], skip_special_tokens = True), '...')