Spaces:
Running
on
Zero
Running
on
Zero
Zenithwang
commited on
Commit
•
bd0098f
1
Parent(s):
72f9be6
Update app.py
Browse files
app.py
CHANGED
@@ -33,7 +33,7 @@ sft_start_token = "<|im_start|>"
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sft_end_token = "<|im_end|>"
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ct_end_token = "<|endoftext|>"
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system_prompt= 'You are a CodeLLM developed by INF.'
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# Function to generate model predictions.
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@@ -45,8 +45,8 @@ def predict(message, history):
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stop = StopOnTokens()
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model_messages = []
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print(f'history: {history}')
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-
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for i, item in enumerate(history):
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model_messages.append({"role": user_role, "content": item[0]})
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model_messages.append({"role": assistant_role, "content": item[1]})
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@@ -55,7 +55,7 @@ def predict(message, history):
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print(f'model_messages: {model_messages}')
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print(f'model_final_inputs: {tokenizer.apply_chat_template(model_messages, add_generation_prompt=True, tokenize=False)}', flush=True)
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model_inputs = tokenizer.apply_chat_template(model_messages, add_generation_prompt=True, return_tensors="pt").to(device)
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# model_inputs = tokenizer([messages], return_tensors="pt").to(device)
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@@ -64,7 +64,8 @@ def predict(message, history):
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input_ids=model_inputs,
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streamer=streamer,
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max_new_tokens=1024,
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do_sample=False
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)
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t = Thread(target=model.generate, kwargs=generate_kwargs)
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@@ -87,24 +88,21 @@ full-height {
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"""
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prompt_examples = [
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'
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'
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'
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'Cách nướng cá'
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]
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placeholder = """
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<div style="opacity: 0.5;">
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<img src="https://
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<br>Sailor models are designed to understand and generate text across diverse linguistic landscapes of these SEA regions:
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<br>🇮🇩Indonesian, 🇹🇭Thai, 🇻🇳Vietnamese, 🇲🇾Malay, and 🇱🇦Lao.
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</div>
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"""
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with gr.Blocks(theme=gr.themes.Soft(), fill_height=True) as demo:
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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>""")
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gr.ChatInterface(predict, chatbot=chatbot, fill_height=True, examples=prompt_examples, css=css)
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demo.launch() # Launching the web interface.
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sft_end_token = "<|im_end|>"
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ct_end_token = "<|endoftext|>"
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# system_prompt= 'You are a CodeLLM developed by INF.'
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# Function to generate model predictions.
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stop = StopOnTokens()
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model_messages = []
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# print(f'history: {history}')
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for i, item in enumerate(history):
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model_messages.append({"role": user_role, "content": item[0]})
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model_messages.append({"role": assistant_role, "content": item[1]})
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print(f'model_messages: {model_messages}')
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# print(f'model_final_inputs: {tokenizer.apply_chat_template(model_messages, add_generation_prompt=True, tokenize=False)}', flush=True)
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model_inputs = tokenizer.apply_chat_template(model_messages, add_generation_prompt=True, return_tensors="pt").to(device)
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# model_inputs = tokenizer([messages], return_tensors="pt").to(device)
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input_ids=model_inputs,
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streamer=streamer,
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max_new_tokens=1024,
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do_sample=False,
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stopping_criteria=StoppingCriteriaList([stop])
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)
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t = Thread(target=model.generate, kwargs=generate_kwargs)
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"""
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prompt_examples = [
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'Write a quick sort algorithm in python.',
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'Write a colorful greedy snake game using pygame.',
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'How to use numpy?'
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]
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placeholder = """
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<div style="opacity: 0.5;">
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<img src="https://github.com/OpenCoder-llm/opencoder-llm.github.io/blob/main/static/images/opencoder_icon.jpg?raw=true" style="width:30%;">
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</div>
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"""
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chatbot = gr.Chatbot(label='OpenCoder', placeholder=placeholder)
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with gr.Blocks(theme=gr.themes.Soft(), fill_height=True) as demo:
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gr.ChatInterface(predict, chatbot=chatbot, fill_height=True, examples=prompt_examples, css=css)
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demo.launch() # Launching the web interface.
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