├── README.md └── src ├── BM25 ├── data │ ├── README.MD │ └── stopword.txt └── main.py ├── Python常用库小例子.md ├── SpatialDropout1D.py ├── baidu_uie.py ├── base64转图片并压缩.py ├── data_loader ├── data │ ├── test.json │ └── train.json ├── readme.md └── 使用datasets加载数据.py ├── doccano_split.py ├── elasticsearch └── python操作elasticsearch.py ├── gradio基本实例.md ├── huggingface ├── 1.pipeline.md ├── 10.model.gnerate.md ├── 11.tansformers中的各种任务.md ├── 12.关于模型的输入和输出.md ├── 13.文本生成的几种方式.md ├── 2.tokenizer.assets │ ├── image-20230427100106028.png │ ├── image-20230427101723165.png │ └── image-20230427111254717.png ├── 2.tokenizer.md ├── 3.datasets.md ├── 4.models.md ├── 5.evaluate.md ├── 6.trainer.assets │ └── image-20230509175119276.png ├── 6.trainer.md ├── 7.data_collator.md ├── 8.optimum.md ├── 9.deepspeed.assets │ ├── image-20230419091554809.png │ ├── image-20230419091718073.png │ └── image-20230419091858240.png ├── 9.deepspeed.md ├── README.MD ├── 实战-BART对联生成.md ├── 实战-GPT2语言模型.md ├── 实战-LoRA微调.md ├── 实战-PPO可控文本生成.md ├── 实战-deepspeed+peft.md ├── 实战-seq2seq_deepspeed.md ├── 实战-中文命名实体识别.md ├── 实战-中文文本摘要.assets │ ├── image-20230427162206189.png │ └── image-20230427162245910.png ├── 实战-中文文本摘要.md ├── 实战-中文阅读理解.md ├── 实战-参数有效微调.md ├── 实战-文本分类.md ├── 实战-英文MASK语言模型.md ├── 实战-英文实体识别.md ├── 实战-英文文本摘要.assets │ └── v2-6b51d2fde0e2bf8a74c02fbef50d397d_720w.webp ├── 实战-英文文本摘要.md ├── 实战-英文翻译为中文.md └── 实战.语言模型代码生成.md ├── interface ├── README.MD ├── __init__.py ├── benchmark.lua ├── locust_test.py ├── restart_server.sh ├── server.log ├── server.py ├── start_server.sh ├── stop_server.sh ├── test_requests.py ├── test_requests.sh ├── test_service_streamer │ ├── __init__.py │ ├── __pycache__ │ │ └── bert_model.cpython-38.pyc │ ├── benchmark.lua │ ├── bert_model.py │ ├── server.log │ ├── server.py │ ├── start_server.sh │ ├── stop_server.sh │ └── wrk_result.txt ├── wrk ├── wrk_result.txt └── wrk_test.sh ├── lcs.py ├── logging记录日志.py ├── loguru打印日志.py ├── losses ├── WBCELoss.py ├── dsc_loss.py ├── focal_loss.py └── smooth_celoss.py ├── mask └── unilm_mask.py ├── models ├── LEAM.py └── transformers.py ├── notebook相关.md ├── play_with_vector ├── __init__.py ├── annoy_vector.py ├── data │ └── readme.md ├── faiss_vector.py ├── gensim_vector.py ├── sklearn_vector.py └── utils.py ├── segment.py ├── simple_lexicon ├── README.MD └── simple_lexicon.py ├── sql.md ├── stanza进行公司名实体识别.md ├── test_fastapi ├── README.MD ├── test.log └── test.py ├── test_flask ├── README.MD ├── gun.py ├── server.py └── test_requests.py ├── test_pypi └── xixiNLP │ ├── LICENSE │ ├── MANIFEST.in │ ├── README.md │ ├── dist │ ├── xixinlp-0.0.1-py3-none-any.whl │ └── xixinlp-0.0.1.tar.gz │ ├── examples │ └── test_seg.py │ ├── setup.py │ ├── test_seg.py │ ├── xixinlp.egg-info │ ├── PKG-INFO │ ├── SOURCES.txt │ ├── dependency_links.txt │ └── top_level.txt │ └── xixinlp │ ├── __init__.py │ ├── __pycache__ │ ├── __init__.cpython-36.pyc │ └── __init__.cpython-38.pyc │ ├── algorithm │ ├── __init__.py │ ├── __pycache__ │ │ ├── __init__.cpython-36.pyc │ │ └── __init__.cpython-38.pyc │ └── seg │ │ ├── __init__.py │ │ ├── __pycache__ │ │ ├── __init__.cpython-36.pyc │ │ ├── __init__.cpython-38.pyc │ │ ├── segment.cpython-36.pyc │ │ └── segment.cpython-38.pyc │ │ ├── seg2 │ │ ├── __init__.py │ │ ├── __pycache__ │ │ │ ├── __init__.cpython-36.pyc │ │ │ ├── __init__.cpython-38.pyc │ │ │ ├── segment2.cpython-36.pyc │ │ │ └── segment2.cpython-38.pyc │ │ └── segment2.py │ │ └── segment.py │ ├── data │ ├── __init__.py │ └── __pycache__ │ │ ├── __init__.cpython-36.pyc │ │ └── __init__.cpython-38.pyc │ ├── gadgat │ ├── __init__.py │ ├── __pycache__ │ │ ├── __init__.cpython-36.pyc │ │ ├── __init__.cpython-38.pyc │ │ ├── extract_time.cpython-36.pyc │ │ └── extract_time.cpython-38.pyc │ └── extract_time.py │ └── utils │ ├── __init__.py │ ├── __pycache__ │ ├── __init__.cpython-36.pyc │ ├── __init__.cpython-38.pyc │ ├── logger.cpython-36.pyc │ ├── logger.cpython-38.pyc │ ├── time_it.cpython-36.pyc │ └── time_it.cpython-38.pyc │ ├── logger.py │ └── time_it.py ├── tokenization ├── test_tokenization.py ├── tokenization.py └── vocab.txt ├── torch分布式推理.py ├── torch版本的UIE实体识别接口.md ├── xixiNLP ├── README.MD ├── examples │ └── test_seg.py ├── test_seg.py └── xixinlp │ ├── __init__.py │ ├── __pycache__ │ └── __init__.cpython-36.pyc │ ├── algorithm │ ├── __init__.py │ ├── __pycache__ │ │ └── __init__.cpython-36.pyc │ └── seg │ │ ├── __init__.py │ │ ├── __pycache__ │ │ ├── __init__.cpython-36.pyc │ │ └── segment.cpython-36.pyc │ │ ├── seg2 │ │ ├── __init__.py │ │ ├── __pycache__ │ │ │ ├── __init__.cpython-36.pyc │ │ │ └── segment2.cpython-36.pyc │ │ └── segment2.py │ │ └── segment.py │ ├── data │ ├── __init__.py │ └── __pycache__ │ │ └── __init__.cpython-36.pyc │ ├── gadgat │ ├── __init__.py │ ├── __pycache__ │ │ ├── __init__.cpython-36.pyc │ │ └── extract_time.cpython-36.pyc │ └── extract_time.py │ └── utils │ ├── __init__.py │ ├── __pycache__ │ ├── __init__.cpython-36.pyc │ ├── logger.cpython-36.pyc │ └── time_it.cpython-36.pyc │ ├── logger.py │ └── time_it.py ├── 中文分句.py ├── 中文分句2.py ├── 中文分句3.py ├── 中英混合实体识别数据预处理.py ├── 使用字形嵌入.py ├── 使用拼音嵌入.py ├── 判断字符是否是中文、英文、数字.py ├── 判断是否是工作日.py ├── 加载词向量.py ├── 基于前缀树的实体识别.py ├── 多GPU数据处理.py ├── 多线程多进程相关 ├── 多线程.py ├── 多进程.py ├── 多进程处理文本例子.py └── 多进程多线程请求vllm.py ├── 多进程分词.py ├── 多进程调用websocket.py ├── 大模型推理 ├── 视觉模型推理.md └── 语言模型推理.md ├── 打印类的属性.py ├── 打印运行时间装饰器.py ├── 捕获具体的异常信息.py ├── 提取qq、微信、支付宝.py ├── 提取车牌号.py ├── 操作mysql.py ├── 文本相似度 ├── tfidf.py └── 词袋结合余弦相似度.py ├── 构建前缀树.py ├── 校阅比对.py ├── 根据地址提取省-市-区-街道.py ├── 根据地址获取经纬度.py ├── 根据字体生成汉字.py ├── 模型部署 ├── bottle.py ├── bottle部署.py └── test_request.py ├── 生成公司logo.py ├── 生成手机号、IMEI、IMSI、MAC.py ├── 自定义argparse.md ├── 英文实体识别标签重整.py ├── 获取天气信息.py ├── 装饰器封装try-except.py ├── 计算词向量间的相似度 ├── README.MD ├── annoy_vector.py ├── data │ └── 占位.txt ├── faiss_vector.py ├── gensim_vector.py ├── sentence_tranformer对比transformers.md ├── sklearn_vector.py ├── utils.py ├── 使用不同向量模型.py └── 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