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import os |
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import time |
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import ftplib |
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import threading |
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from tqdm.notebook import tqdm |
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import zipfile |
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import gradio as gr |
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import torch |
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from transformers import AutoTokenizer, AutoModel |
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def get_model_ftp(model_path, model_name): |
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ftp = ftplib.FTP('10.209.16.22') |
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ftp.login('soltest', 'soltest') |
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folder_path = '/ftp/3D/ai-model/ChatYuan/ClueAI/' |
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ftp.cwd(folder_path) |
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file_list = ftp.nlst(folder_path) |
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if os.path.join(folder_path, model_name) in file_list: |
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file_size = ftp.size(model_name) |
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with open(os.path.join(model_path, model_name), 'wb') as f: |
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with tqdm.wrapattr(f, 'write', desc="Download " + model_name, total=file_size, unit='B', unit_scale=True) as pbar: |
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ftp.retrbinary('RETR ' + model_name, pbar.write) |
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ftp.quit() |
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unzip(model_path, model_name) |
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def unzip(path, file_name): |
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try: |
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stop_unzip = threading.Event() |
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thread = threading.Thread(target=print_flush, args=(stop_unzip, "start decompression ")) |
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thread.start() |
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zip_file = zipfile.ZipFile(os.path.join(path, file_name)) |
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for names in zip_file.namelist(): |
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zip_file.extract(names, path) |
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zip_file.close() |
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stop_unzip.set() |
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thread.join() |
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except Exception as ex: |
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stop_unzip.set() |
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thread.join() |
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os.remove(os.path.join(path, file_name)) |
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raise Exception(f"\nunzip失败：" + str(ex)) |
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def prepare_model(model_dir): |
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model_path = model_dir.split('/')[0] |
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model_name = model_dir.split('/')[1] |
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if not os.path.exists(model_dir): |
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os.makedirs("ClueAI", exist_ok=True) |
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get_model_ftp(model_path, model_name + '.zip') |
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os.remove(os.path.join(model_path, model_name + '.zip')) |
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def print_flush(stop_event, str): |
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loading_strings = [str + ".", str + "..", str + "...", str + ".", str + "..", str + "..."] |
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index = 0 |
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while not stop_event.is_set(): |
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loading_str = loading_strings[index] |
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print(loading_str, end="\r") |
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index = (index + 1) % len(loading_strings) |
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time.sleep(0.5) |
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if index == 0: |
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print(" " * len(loading_str), end="\r") |
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time.sleep(0.2) |
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print(loading_strings[index], end="\r") |
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print("\n" + str.split(" ")[1] + " finish.") |
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model_dir = 'ClueAI/ChatYuan-large-v2' |
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prepare_model(model_dir) |
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tokenizer = AutoTokenizer.from_pretrained(model_dir) |
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model = AutoModel.from_pretrained(model_dir, trust_remote_code=True) |
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device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') |
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model.to(device) |
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def preprocess(text): |
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base_info = "" |
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text = f"{base_info}{text}" |
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text = text.replace("\n", "\\n").replace("\t", "\\t") |
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return text |
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def postprocess(text): |
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return text.replace("\\n", "\n").replace("\\t", "\t").replace( |
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'%20', ' ') |
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generate_config = { |
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'do_sample': True, |
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'top_p': 0.9, |
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'top_k': 50, |
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'temperature': 0.7, |
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'num_beams': 1, |
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'max_length': 1024, |
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'min_length': 3, |
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'no_repeat_ngram_size': 5, |
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'length_penalty': 0.6, |
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'return_dict_in_generate': True, |
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'output_scores': True |
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} |
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def answer( |
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text, |
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top_p, |
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temperature, |
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sample=True, |
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): |
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''' |
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sample：是否抽样。生成任务，可以设置为True; |
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top_p：0-1之间，生成的内容越多样 |
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''' |
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text = preprocess(text) |
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encoding = tokenizer(text=[text], |
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truncation=True, |
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padding=True, |
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max_length=1024, |
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return_tensors="pt").to(device) |
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if not sample: |
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out = model.generate(**encoding, |
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return_dict_in_generate=True, |
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output_scores=False, |
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max_new_tokens=1024, |
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num_beams=1, |
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length_penalty=0.6) |
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else: |
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out = model.generate(**encoding, |
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return_dict_in_generate=True, |
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output_scores=False, |
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max_new_tokens=1024, |
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do_sample=True, |
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top_p=top_p, |
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temperature=temperature, |
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no_repeat_ngram_size=12) |
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out_text = tokenizer.batch_decode(out["sequences"], |
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skip_special_tokens=True) |
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return postprocess(out_text[0]) |
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def clear_session(): |
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return '', None |
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def chatyuan_bot(input, history, top_p, temperature, num): |
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history = history or [] |
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if len(history) > num: |
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history = history[-num:] |
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context = "\n".join([ |
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f"用户：{input_text}\n小元：{answer_text}" |
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for input_text, answer_text in history |
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]) |
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input_text = context + "\n用户：" + input + "\n小元：" |
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input_text = input_text.strip() |
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output_text = answer(input_text, top_p, temperature) |
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print("open_model".center(20, "=")) |
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print(f"{input_text}\n{output_text}") |
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history.append((input, output_text)) |
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return '', history, history |
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def chatyuan_bot_regenerate(input, history, top_p, temperature, num): |
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history = history or [] |
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if history: |
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input = history[-1][0] |
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history = history[:-1] |
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if len(history) > num: |
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history = history[-num:] |
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context = "\n".join([ |
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f"用户：{input_text}\n小元：{answer_text}" |
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for input_text, answer_text in history |
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]) |
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input_text = context + "\n用户：" + input + "\n小元：" |
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input_text = input_text.strip() |
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output_text = answer(input_text, top_p, temperature) |
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print("open_model".center(20, "=")) |
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print(f"{input_text}\n{output_text}") |
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history.append((input, output_text)) |
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return '', history, history |
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block = gr.Blocks() |
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with block as demo: |
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gr.Markdown("""<h1><center>元语智能——ChatYuan</center></h1> |
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<font size=4>回答来自ChatYuan, 是模型生成的结果, 请谨慎辨别和参考, 不代表任何人观点 | Answer generated by ChatYuan model</font> |
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<font size=4>注意：gradio对markdown代码格式展示有限</font> |
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""") |
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with gr.Row(): |
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with gr.Column(scale=3): |
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chatbot = gr.Chatbot(label='ChatYuan').style(height=400) |
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with gr.Column(scale=1): |
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num = gr.Slider(minimum=4, |
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maximum=10, |
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label="最大的对话轮数", |
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value=5, |
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step=1) |
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top_p = gr.Slider(minimum=0, |
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maximum=1, |
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label="top_p", |
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value=1, |
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step=0.1) |
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temperature = gr.Slider(minimum=0, |
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maximum=1, |
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label="temperature", |
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value=0.7, |
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step=0.1) |
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clear_history = gr.Button("👋 清除历史对话 | Clear History") |
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send = gr.Button("🚀 发送 | Send") |
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regenerate = gr.Button("🚀 重新生成本次结果 | regenerate") |
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message = gr.Textbox() |
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state = gr.State() |
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message.submit(chatyuan_bot, |
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inputs=[message, state, top_p, temperature, num], |
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outputs=[message, chatbot, state]) |
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regenerate.click(chatyuan_bot_regenerate, |
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inputs=[message, state, top_p, temperature, num], |
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outputs=[message, chatbot, state]) |
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send.click(chatyuan_bot, |
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inputs=[message, state, top_p, temperature, num], |
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outputs=[message, chatbot, state]) |
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clear_history.click(fn=clear_session, |
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inputs=[], |
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outputs=[chatbot, state], |
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queue=False) |
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block = gr.Blocks() |
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with block as introduction: |
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gr.Markdown("""<h1><center>元语智能——ChatYuan</center></h1> |
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<font size=4>😉ChatYuan: 元语功能型对话大模型 | General Model for Dialogue with ChatYuan |
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<br> |
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👏ChatYuan-large-v2是一个支持中英双语的功能型对话语言大模型，是继ChatYuan系列中ChatYuan-large-v1开源后的又一个开源模型。ChatYuan-large-v2使用了和 v1版本相同的技术方案，在微调数据、人类反馈强化学习、思维链等方面进行了优化。 |
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<br> |
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ChatYuan large v2 is an open-source large language model for dialogue, supports both Chinese and English languages, and in ChatGPT style. |
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<br> |
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ChatYuan-large-v2是ChatYuan系列中以轻量化实现高质量效果的模型之一，用户可以在消费级显卡、 PC甚至手机上进行推理（INT4 最低只需 400M ）。 |
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<br> |
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在Chatyuan-large-v1的原有功能的基础上，我们给模型进行了如下优化： |
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- 新增了中英双语对话能力。 |
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- 新增了拒答能力。对于一些危险、有害的问题，学会了拒答处理。 |
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- 新增了代码生成功能。对于基础代码生成进行了一定程度优化。 |
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- 增强了基础能力。原有上下文问答、创意性写作能力明显提升。 |
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- 新增了表格生成功能。使生成的表格内容和格式更适配。 |
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- 增强了基础数学运算能力。 |
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- 最大长度token数扩展到4096。 |
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- 增强了模拟情景能力。.<br> |
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<br> |
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Based on the original functions of Chatyuan-large-v1, we optimized the model as follows: |
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-Added the ability to speak in both Chinese and English. |
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-Added the ability to refuse to answer. Learn to refuse to answer some dangerous and harmful questions. |
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-Added code generation functionality. Basic code generation has been optimized to a certain extent. |
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-Enhanced basic capabilities. The original contextual Q&A and creative writing skills have significantly improved. |
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-Added a table generation function. Make the generated table content and format more appropriate. |
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-Enhanced basic mathematical computing capabilities. |
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-The maximum number of length tokens has been expanded to 4096. |
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-Enhanced ability to simulate scenarios< br> |
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<br> |
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👀<a href='https://www.cluebenchmarks.com/clueai.html'>PromptCLUE-large</a>在1000亿token中文语料上预训练, 累计学习1.5万亿中文token, 并且在数百种任务上进行Prompt任务式训练. 针对理解类任务, 如分类、情感分析、抽取等, 可以自定义标签体系; 针对多种生成任务, 可以进行采样自由生成. <br> |
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<br> |
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<a href='https://modelscope.cn/models/ClueAI/ChatYuan-large/summary' target="_blank">ModelScope</a> | <a href='https://huggingface.co/ClueAI/ChatYuan-large-v1' target="_blank">Huggingface</a> | <a href='https://www.clueai.cn' target="_blank">官网体验场</a> | <a href='https://github.com/clue-ai/clueai-python#ChatYuan%E5%8A%9F%E8%83%BD%E5%AF%B9%E8%AF%9D' target="_blank">ChatYuan-API</a> | <a href='https://github.com/clue-ai/ChatYuan' target="_blank">Github项目地址</a> | <a href='https://openi.pcl.ac.cn/ChatYuan/ChatYuan/src/branch/main/Fine_tuning_ChatYuan_large_with_pCLUE.ipynb' target="_blank">OpenI免费试用</a> |
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</font> |
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<center><a href="https://clustrmaps.com/site/1bts0" title="Visit tracker"><img src="//www.clustrmaps.com/map_v2.png?d=ycVCe17noTYFDs30w7AmkFaE-TwabMBukDP1802_Lts&cl=ffffff" /></a></center> |
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""") |
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gui = gr.TabbedInterface( |
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interface_list=[introduction, demo], |
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tab_names=["相关介绍 | Introduction", "开源模型 | Online Demo"]) |
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