Adding code to download baseline model.

app.py

@@ -1,5 +1,4 @@
 import streamlit as st
-import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
 from transformers import pipeline
 
@@ -26,7 +25,7 @@ model_id = "niclasfw/schlager-bot-004"
 model = AutoModelForCausalLM.from_pretrained(model_id)
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 
-generator = pipeline(task="text-generation", model=model_id, tokenizer=model_id)
+# generator = pipeline(task="text-generation", model=model_id, tokenizer=model_id)
 
 st.title('Schlager Bot')
 user_input = st.text_area('Enter verse (minimum of 15 words): ')
@@ -42,13 +41,13 @@ if user_input and button:
 
     ### Response:
     """
-    output = generator(prompt, do_sample=True, max_new_tokens=500, top_p=0.75, temperature=0.95, top_k=15)
+    # output = generator(prompt, do_sample=True, max_new_tokens=500, top_p=0.75, temperature=0.95, top_k=15)
     # st.write("Prompt: ", user_input)
     # input = tokenizer(prompt, padding=True, return_tensors="pt")
     # generate_ids = model.generate(input.input_ids, max_length=500, top_p=0.75, temperature=0.95, top_k=15)
     # output = tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
-    # input_ids = tokenizer(prompt, return_tensors="pt", truncation=True)
-    # outputs = model.generate(input_ids=input_ids, pad_token_id=tokenizer.eos_token_id, max_new_tokens=500, do_sample=True, top_p=0.75, temperature=0.95, top_k=15)
+    input_ids = tokenizer(prompt, return_tensors="pt", truncation=True)
+    outputs = model.generate(input_ids=input_ids, pad_token_id=tokenizer.eos_token_id, max_new_tokens=500, do_sample=True, top_p=0.75, temperature=0.95, top_k=15)
 
     st.write(output)