Update app.py

app.py

@@ -4,7 +4,9 @@ import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer, StoppingCriteria, StoppingCriteriaList, TextIteratorStreamer
 from threading import Thread
 
-model_path = 'sail/Sailor-7B-Chat'
+# model_path = 'sail/Sailor-7B-Chat'
+model_path = 'sail/Sailor2-20B-Chat'
+
 
 # Loading the tokenizer and model from Hugging Face's model hub.
 tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
@@ -24,18 +26,28 @@ class StopOnTokens(StoppingCriteria):
         return False
 
 
+# system_role= 'system'
+# user_role = 'question'
+# assistant_role = "answer"
+
 system_role= 'system'
-user_role = 'question'
-assistant_role = "answer"
+user_role = 'user'
+assistant_role = 'assistant'
 
 sft_start_token =  "<|im_start|>"
 sft_end_token = "<|im_end|>"
 ct_end_token = "<|endoftext|>"
 
+# system_prompt= \
+# 'You are an AI assistant named Sailor created by Sea AI Lab. \
+# Your answer should be friendly, unbiased, faithful, informative and detailed.'
+# system_prompt = f"<|im_start|>{system_role}\n{system_prompt}<|im_end|>"
+
 system_prompt= \
-'You are an AI assistant named Sailor created by Sea AI Lab. \
-Your answer should be friendly, unbiased, faithful, informative and detailed.'
-system_prompt = f"<|im_start|>{system_role}\n{system_prompt}<|im_end|>"
+'You are an AI assistant named Sailor2, created by Sea AI Lab. \
+As an AI assistant, you can answer questions in English, Chinese, and Southeast Asian languages \
+such as Burmese, Cebuano, Ilocano, Indonesian, Javanese, Khmer, Lao, Malay, Sundanese, Tagalog, Thai, Vietnamese, and Waray. \
+Your responses should be friendly, unbiased, informative, detailed, and faithful.'
 
 # Function to generate model predictions.
 
@@ -85,18 +97,20 @@ prompt_examples = [
     'Cách nướng cá'
 ]
 
-placeholder = """
-<div style="opacity: 0.5;">
-    <img src="https://raw.githubusercontent.com/sail-sg/sailor-llm/main/misc/banner.jpg" style="width:30%;">
-    <br>Sailor models are designed to understand and generate text across diverse linguistic landscapes of these SEA regions:
-    <br>🇮🇩Indonesian, 🇹🇭Thai, 🇻🇳Vietnamese, 🇲🇾Malay, and 🇱🇦Lao.
-</div>
-"""
+# placeholder = """
+# <div style="opacity: 0.5;">
+#     <img src="https://raw.githubusercontent.com/sail-sg/sailor-llm/main/misc/banner.jpg" style="width:30%;">
+#     <br>Sailor models are designed to understand and generate text across diverse linguistic landscapes of these SEA regions:
+#     <br>🇮🇩Indonesian, 🇹🇭Thai, 🇻🇳Vietnamese, 🇲🇾Malay, and 🇱🇦Lao.
+# </div>
+# """
+placeholder=''
 
-chatbot = gr.Chatbot(label='Sailor', placeholder=placeholder) 
+chatbot = gr.Chatbot(label='Sailor2', placeholder=placeholder) 
 with gr.Blocks(theme=gr.themes.Soft(), fill_height=True) as demo:
     # gr.Markdown("""<center><font size=8>Sailor-Chat Bot⚓</center>""")
-    gr.Markdown("""<p align="center"><img src="https://github.com/sail-sg/sailor-llm/raw/main/misc/wide_sailor_banner.jpg" style="height: 110px"/><p>""")
+    # gr.Markdown("""<p align="center"><img src="https://github.com/sail-sg/sailor-llm/raw/main/misc/wide_sailor_banner.jpg" style="height: 110px"/><p>""")
+    gr.Markdown("""<p align="center"><img src="https://github.com/sail-sg/sailor2/raw/main/misc/sailor2_wide_banner.jpg" style="height: 110px"/><p>""")
     gr.ChatInterface(predict, chatbot=chatbot, fill_height=True, examples=prompt_examples, css=css)
 
     demo.launch()  # Launching the web interface.