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@ -9,12 +9,23 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
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from transformers.generation import GenerationConfig
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import sys
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tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen-7B-Chat", trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen-7B-Chat", device_map="auto", trust_remote_code=True).eval()
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model.generation_config = GenerationConfig.from_pretrained("Qwen/Qwen-7B-Chat", trust_remote_code=True)
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tokenizer = AutoTokenizer.from_pretrained(
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"Qwen/Qwen-7B-Chat", trust_remote_code=True, resume_download=True
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)
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model = AutoModelForCausalLM.from_pretrained(
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"Qwen/Qwen-7B-Chat",
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device_map="auto",
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offload_folder="offload",
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trust_remote_code=True,
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resume_download=True,
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).eval()
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model.generation_config = GenerationConfig.from_pretrained(
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"Qwen/Qwen-7B-Chat", trust_remote_code=True, resume_download=True
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)
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if len(sys.argv) > 1 and sys.argv[1] == "--exit":
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exit(0)
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sys.exit(0)
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def postprocess(self, y):
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if y is None:
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@ -58,21 +69,26 @@ def parse_text(text):
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line = line.replace("(", "(")
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line = line.replace(")", ")")
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line = line.replace("$", "$")
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lines[i] = "<br>"+line
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lines[i] = "<br>" + line
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text = "".join(lines)
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return text
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def predict(input, chatbot, history, past_key_values):
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task_history = []
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def predict(input, chatbot):
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print('Q: ' + parse_text(input))
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chatbot.append((parse_text(input), ""))
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fullResponse = "";
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fullResponse = ""
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for response in model.chat(tokenizer, input, history=history, stream=True):
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for response in model.chat(tokenizer, input, history=task_history, stream=True):
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chatbot[-1] = (parse_text(input), parse_text(response))
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yield chatbot, history, past_key_values
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fullResponse = parse_text(response);
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yield chatbot
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fullResponse = parse_text(response)
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task_history.append((input, fullResponse))
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print("A: " + parse_text(fullResponse))
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@ -81,7 +97,8 @@ def reset_user_input():
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def reset_state():
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return [], [], None
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task_history = []
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return []
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with gr.Blocks() as demo:
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@ -91,19 +108,16 @@ with gr.Blocks() as demo:
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with gr.Row():
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with gr.Column(scale=4):
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with gr.Column(scale=12):
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user_input = gr.Textbox(show_label=False, placeholder="Input...", lines=10).style(
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container=False)
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query = gr.Textbox(
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show_label=False, placeholder="Input...", lines=10
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).style(container=False)
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with gr.Column(min_width=32, scale=1):
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submitBtn = gr.Button("Submit", variant="primary")
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with gr.Column(scale=1):
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emptyBtn = gr.Button("Clear History")
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history = gr.State([])
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past_key_values = gr.State(None)
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submitBtn.click(predict, [user_input, chatbot, history, past_key_values],
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[chatbot, history, past_key_values], show_progress=True)
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submitBtn.click(reset_user_input, [], [user_input])
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emptyBtn.click(reset_state, outputs=[chatbot, history, past_key_values], show_progress=True)
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submitBtn.click(predict, [query, chatbot], [chatbot], show_progress=True)
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submitBtn.click(reset_user_input, [], [query])
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emptyBtn.click(reset_state, outputs=[chatbot], show_progress=True)
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demo.queue().launch(share=False, inbrowser=True, server_port=80, server_name="0.0.0.0")
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