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| import psutil | |
| import gradio as gr | |
| from functools import partial | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
| mem = psutil.virtual_memory() | |
| tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) | |
| model = AutoModelForSeq2SeqLM.from_pretrained("THUDM/chatglm-6b-int4", trust_remote_code=True).quantize(bits=4, compile_parallel_kernel=True, parallel_num=2).cpu().float() | |
| def chat(query, history=[]): | |
| _, history = model.chat(tokenizer, query, history, max_length=512) | |
| return history, history | |
| description = "This is an unofficial chatbot application based on open source model ChatGLM-6B(https://github.com/THUDM/ChatGLM-6B), running on cpu(therefore max_length is limited to 512). \nIf you want to use this chat bot in your space, 'Duplicate this space' by click the button close to 'Linked Models'. \n" | |
| title = "ChatGLM-6B Chatbot" | |
| examples = [["Hello?"], ["你好。"], ["介绍清华"]] | |
| chatbot_interface = gr.Interface( | |
| fn=chat, | |
| title=title, | |
| description=description, | |
| examples=examples, | |
| inputs=["text", "state"], | |
| outputs=["chatbot", "state"] | |
| ) | |
| chatbot_interface.launch() | |