Create app.py

app.py

@@ -0,0 +1,26 @@
+import streamlit as st
+import time
+from datetime import datetime
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+@st.cache(allow_output_mutation=True)
+def opt_model(prompt, num_sequences = 1, max_length = 50):  
+    model = AutoModelForCausalLM.from_pretrained("facebook/opt-30b", torch_dtype=torch.float16).cuda()
+    tokenizer = AutoTokenizer.from_pretrained("facebook/opt-30b", use_fast=False)
+    input_ids = tokenizer(prompt, return_tensors="pt").input_ids.cuda()
+    generated_ids = model.generate(input_ids, num_return_sequences=num_sequences, max_length=max_length)
+    answer = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
+    return answer
+
+prompt= st.text_area('Your prompt here',
+ '''Hello, I'm am conscious and''')
+
+answer = opt_model(prompt)
+#lst = ['ciao come stai sjfsbd dfhsdf  fuahfuf  feuhfu wefwu ']
+lst = ' '.join(answer)
+
+t = st.empty()
+for i in range(len(lst)):
+    t.markdown("### %s..." % lst[0:i])
+    time.sleep(0.04)