Update app.py

app.py

@@ -12,6 +12,7 @@ MODEL = "LLaMAX/LLaMAX2-7B-Alpaca"
 RELATIVE_MODEL="LLaMAX/LLaMAX2-7B"
 
 TITLE = "<h1><center>LLaMAX Translator</center></h1>"
+DESCRIPTION ="<center>Do tài chính có hạn nên dự án đang chỉ dùng CPU để xử lý yêu cầu. Để xử lý với tốc độ nhanh hơn thông qua GPU, vui lòng truy cập vào notebook Kaggle sau <a href="https://www.kaggle.com/code/naofunyannn/llamax-translation">LLaMAX3 Translator> </center>"
 
 
 model = AutoModelForCausalLM.from_pretrained(
@@ -49,8 +50,8 @@ def chunk_text():
 
 # Function to calculate BLEU score
 def calculate_bleu_score(candidate: str, references: list):
-    candidate_tokens = candidate.split()  # Tokenizing the candidate output
-    bleu_score = sentence_bleu(references, candidate_tokens)  # Calculating BLEU score
+    candidate_tokens = candidate.split() 
+    bleu_score = sentence_bleu(references, candidate_tokens)
     return bleu_score
     
 @spaces.GPU(duration=60)
@@ -83,19 +84,9 @@ def translate(
     
     resp = tokenizer.decode(outputs[0], skip_special_tokens=True, clean_up_tokenization_spaces=False)
     
-    #yield resp[len(prompt):]
     # Calculate BLEU score
-    '''
-    references = [
-        'this is a dog'.split(),
-        'it is dog'.split(),
-        'dog it is'.split(),
-        'a dog, it is'.split() 
-    ]
-    bleu_score = calculate_bleu_score(resp[len(prompt):], references)  # Calculate BLEU score
-    '''
-    references = [resp[len(prompt):].split()]  # Use the generated response as the reference
-    bleu_score = calculate_bleu_score(resp[len(prompt):], references)  # Calculate BLEU score
+    references = [resp[len(prompt):].split()] 
+    bleu_score = calculate_bleu_score(resp[len(prompt):], references)
 
     yield resp[len(prompt):], bleu_score
 
@@ -114,7 +105,7 @@ CSS = """
 """
 
 LICENSE = """
-Model: <a href="https://huggingface.co/LLaMAX/LLaMAX3-8B-Alpaca">LLaMAX3-8B-Alpaca</a>
+Model: <a href="https://huggingface.co/LLaMAX/LLaMAX2-7B-Alpaca">LLaMAX2-7B-Alpaca</a>
 """
 
 LANG_LIST = ['Akrikaans', 'Amharic', 'Arabic', 'Armenian', 'Assamese', 'Asturian', 'Azerbaijani', \
@@ -145,9 +136,7 @@ with gr.Blocks(theme="soft", css=CSS) as demo:
         with gr.Column(scale=4):
             source_text = gr.Textbox(
                 label="Văn bản gốc",
-                value="LLaMAX is a language model with powerful multilingual capabilities without loss instruction-following capabilities. "+\
-                "LLaMAX supports translation between more than 100 languages, "+\
-                "surpassing the performance of similarly scaled LLMs.",
+                value="Hello",
                 lines=10,
             )
             output_text = gr.Textbox(
@@ -156,7 +145,7 @@ with gr.Blocks(theme="soft", css=CSS) as demo:
                 show_copy_button=True,
             )
 
-            bleu_score_output = gr.Textbox(  # New holder area for BLEU score
+            bleu_score_output = gr.Textbox(
                 label="BLEU Score",
                 lines=10,
                 interactive=False,
@@ -181,7 +170,7 @@ with gr.Blocks(theme="soft", css=CSS) as demo:
                 step=8,
             )
             temperature = gr.Slider(
-                label="Temperature",
+                label="Độ sáng tạo",
                 minimum=0,
                 maximum=1,
                 value=0.3,
@@ -234,7 +223,6 @@ Write a response that ensuring accuracy and maintaining the tone and style of th
     gr.Markdown(LICENSE)
     
     #source_text.change(lang_detector, source_text, source_lang)
-    #submit.click(fn=translate, inputs=[source_text, source_lang, target_lang, inst, prompt, max_length, temperature, top_p, rp], outputs=[output_text])
     submit.click(fn=translate, inputs=[source_text, source_lang, target_lang, inst, prompt, max_length, temperature, top_p, rp], outputs=[output_text, bleu_score_output])
 
 if __name__ == "__main__":