Updated App name and text to reflect the model being used

README.md

@@ -1,5 +1,5 @@
 ---
-title: Hebrew Poetry - GPT Neo (Small)
+title: Hebrew GPT Neo (Small)
 emoji: 📚
 colorFrom: blue
 colorTo: gray

app.py

@@ -74,10 +74,10 @@ def extend(input_text, max_size=20, top_k=50, top_p=0.95):
 
 
 if __name__ == "__main__":
-    st.title("Hebrew Poetry - GPT Neo (Small)")
+    st.title("Hebrew GPT Neo (Small)")
 
-    model, tokenizer = load_model("Norod78/hebrew-gpt_neo-small")
-    #model, tokenizer = load_model("Norod78/hebrew_poetry-gpt_neo-tiny")
+    tokenizer = AutoTokenizer.from_pretrained("Norod78/hebrew-gpt_neo-small")
+    model = AutoModelForCausalLM.from_pretrained("Norod78/hebrew-gpt_neo-small")
 
     stop_token = "<|endoftext|>"
     new_lines = "\n\n\n"
@@ -101,7 +101,7 @@ if __name__ == "__main__":
     top_p = st.sidebar.slider("Top-P", 0.0, 1.0, 0.95, help="If set to float < 1, only the most probable tokens with probabilities that add up to top_p or higher are kept for generation.")
 
     st.markdown(    
-        """Hebrew poetry text generation model based on EleutherAI's gpt-neo. Each was trained on a TPUv3-8 which was made avilable to me via the [TPU Research Cloud Program](https://sites.research.google/trc/). """
+        """Hebrew text generation model based on EleutherAI's gpt-neo. Each was trained on a TPUv3-8 which was made avilable to me via the [TPU Research Cloud Program](https://sites.research.google/trc/). """
     )
 
     prompt = "האיש האחרון בעולם ישב לבד בחדרו כשלפתע נשמעה נקישה"
@@ -121,4 +121,6 @@ if __name__ == "__main__":
             st.markdown(f"<p dir=\"rtl\" style=\"text-align:right;\"> {result} </p>", unsafe_allow_html=True)
             st.write("\n\nResult length: " + str(len(result)) + " bytes")
             print(f"\"{result}\"")
+    
+    st.markdown("<footer><hr><p style=\"font-size:12px\">By <a href=\"https://linktr.ee/Norod78\">Doron Adler</a></p></footer> ", unsafe_allow_html=True)
 

requirements.txt

@@ -1,4 +1,4 @@
-streamlit==0.80.0
+streamlit
 transformers
 tokenizers
 torch