update

2024.01.27_chat.guanjihuan.com/使用 Transformer 软件包调用开源模型 Qwen/Qwen.py

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+"""
+This code is supported by the website: https://www.guanjihuan.com
+The newest version of this code is on the web page: https://www.guanjihuan.com/archives/38502
+"""
+
+import streamlit as st
+st.set_page_config(
+    page_title="Chat",
+    layout='wide'
+)
+
+choose_load_model = 0  # 选择加载的模型（Qwen-7B 或 Qwen-14B）
+
+if choose_load_model == 0:
+    # Qwen-7B（需要8G显存）
+    @st.cache_resource
+    def load_model_qwen_7B():
+        from transformers import AutoTokenizer, AutoModelForCausalLM
+        tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen-7B-Chat-Int4", trust_remote_code=True)
+        model = AutoModelForCausalLM.from_pretrained(
+            "Qwen/Qwen-7B-Chat-Int4",
+            device_map="auto",
+            trust_remote_code=True,
+        ).eval()
+        return tokenizer, model
+    tokenizer_qwen_7B, model_qwen_7B = load_model_qwen_7B()
+
+elif choose_load_model == 1:
+    # Qwen-14B（需要12G显存）
+    @st.cache_resource
+    def load_model_qwen_14B():
+        from transformers import AutoTokenizer, AutoModelForCausalLM
+        tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen-14B-Chat-Int4", trust_remote_code=True)
+        model = AutoModelForCausalLM.from_pretrained(
+            "Qwen/Qwen-14B-Chat-Int4",
+            device_map="auto",
+            trust_remote_code=True
+        ).eval()
+        return tokenizer, model
+    tokenizer_qwen_14B, model_qwen_14B = load_model_qwen_14B()
+
+with st.sidebar:
+    with st.expander('参数', expanded=True):
+        max_length = 409600
+        top_p = st.slider('top_p', 0.01, 1.0, step=0.01, value=0.8, key='top_p_session')
+        temperature = st.slider('temperature', 0.51, 1.0, step=0.01, value=0.8, key='temperature_session') 
+        def reset_parameter():
+            st.session_state['top_p_session'] = 0.8
+            st.session_state['temperature_session'] = 0.8
+        reset_parameter_button = st.button('重置', on_click=reset_parameter)
+
+prompt = st.chat_input("在这里输入您的命令")
+
+from transformers.generation import GenerationConfig
+
+if choose_load_model == 0:
+    config_qwen_7b = GenerationConfig.from_pretrained(
+        "Qwen/Qwen-7B-Chat-Int4", trust_remote_code=True, resume_download=True, max_length = max_length, top_p = top_p, temperature = temperature
+    )
+    def chat_response_qwen_7B(query):
+        for response in model_qwen_7B.chat_stream(tokenizer_qwen_7B, query, history=st.session_state.history_qwen, generation_config=config_qwen_7b):
+            message_placeholder_qwen.markdown(response)
+            if stop_button:
+                break
+        st.session_state.history_qwen.append((query, response))
+        st.session_state.ai_response.append({"role": "robot", "content": response, "avatar": "assistant"})
+        return response
+
+elif choose_load_model == 1:
+    config_qwen_14b = GenerationConfig.from_pretrained(
+        "Qwen/Qwen-14B-Chat-Int4", trust_remote_code=True, resume_download=True, max_length = max_length, top_p = top_p, temperature = temperature
+    )
+    def chat_response_qwen_14B(query):
+        for response in model_qwen_14B.chat_stream(tokenizer_qwen_14B, query, history=st.session_state.history_qwen, generation_config=config_qwen_14b):
+            message_placeholder_qwen.markdown(response)
+            if stop_button:
+                break
+        st.session_state.history_qwen.append((query, response))
+        st.session_state.ai_response.append({"role": "robot", "content": response, "avatar": "assistant"})
+        return response
+
+def clear_all():
+    st.session_state.history_qwen = []
+    st.session_state.ai_response = []
+
+if 'history_qwen' not in st.session_state:
+    st.session_state.history_qwen = []
+if 'ai_response' not in st.session_state:
+    st.session_state.ai_response = []
+
+for ai_response in st.session_state.ai_response:
+    with st.chat_message(ai_response["role"], avatar=ai_response.get("avatar")):
+        st.markdown(ai_response["content"])
+
+prompt_placeholder = st.chat_message("user", avatar='user')
+with st.chat_message("robot", avatar="assistant"):
+    message_placeholder_qwen = st.empty()
+
+if prompt:
+    prompt_placeholder.markdown(prompt)
+    st.session_state.ai_response.append({"role": "user", "content": prompt, "avatar": 'user'})
+    stop = st.empty()
+    stop_button = stop.button('停止', key='break_response')
+    if choose_load_model == 0:
+        chat_response_qwen_7B(prompt)
+    elif choose_load_model == 1:
+        chat_response_qwen_14B(prompt)
+    stop.empty()
+button_clear = st.button("清空", on_click=clear_all, key='clear')