updated app

app.py

@@ -2,7 +2,12 @@ import streamlit as st
 from transformers import AutoTokenizer,AutoModelForSeq2SeqLM
 
 @st.cache(persist=True)
-def load_model(input_complex_sentence,model, tokenizer):
+def load_model(input_complex_sentence,model):
+	
+	base_path = "flax-community/"
+	model_path = base_path + model
+	tokenizer = AutoTokenizer.from_pretrained(model_path)
+	model     = AutoModelForSeq2SeqLM.from_pretrained(model_path)
 	
 	tokenized_sentence = tokenizer(input_complex_sentence,return_tensors="pt")
 	result = model.generate(tokenized_sentence['input_ids'],attention_mask = tokenized_sentence['attention_mask'],max_length=256,num_beams=5)
@@ -12,22 +17,6 @@ def load_model(input_complex_sentence,model, tokenizer):
 
 def main():
 
-	t5_base_path = "flax-community/t5-base-wikisplit"
-	t5_base_tokenizer = AutoTokenizer.from_pretrained(t5_base_path)
-	t5_base_model     = AutoModelForSeq2SeqLM.from_pretrained(t5_base_path)
-
-	t5_v1_1_base_path = "flax-community/t5-v1_1-base-wikisplit"
-	t5_v1_1_base_tokenizer = AutoTokenizer.from_pretrained(t5_v1_1_base_path)
-	t5_v1_1_base_model     = AutoModelForSeq2SeqLM.from_pretrained(t5_v1_1_base_path)
-
-	byt5_base_path = "flax-community/byt5-base-wikisplit"
-	byt5_base_tokenizer = AutoTokenizer.from_pretrained(byt5_base_path)
-	byt5_base_model     = AutoModelForSeq2SeqLM.from_pretrained(byt5_base_path)
-
-	t5_large_path = "flax-community/t5-large-wikisplit"
-	t5_large_tokenizer = AutoTokenizer.from_pretrained(t5_large_path)
-	t5_large_model     = AutoModelForSeq2SeqLM.from_pretrained(t5_large_path)
-
 	st.title("✂️ Sentence Split in English using T5 variants")
 	st.write("Sentence Split is the task of dividing a long Sentence into multiple Sentences")
 	
@@ -40,15 +29,8 @@ def main():
 	input_complex_sentence = st.text_area("Please type a long Sentence to split",example)
 
 	if st.button('Simplify'):
-		
-		if model=="t5-base-wikisplit":
-			generated_sentence = load_model(input_complex_sentence, t5_base_model, t5_base_tokenizer)
-		elif model=="t5-v1_1-base-wikisplit":
-			generated_sentence = load_model(input_complex_sentence, t5_v1_1_base_model, t5_v1_1_base_tokenizer)
-		elif model=="byt5-base-wikisplit":
-			generated_sentence = load_model(input_complex_sentence, byt5_base_model, byt5_base_tokenizer)
-		else:
-			generated_sentence = load_model(input_complex_sentence, t5_large_model, t5_large_tokenizer)
+ 
+		generated_sentence = load_model(input_complex_sentence, model)
 		st.write(generated_sentence)