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AI-generated-text-detection-pair

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metadata
license: mit
language:
  - zh
metrics:
  - accuracy
pipeline_tag: text-classification
widget:
  - text: >-
      李白（701年2月28日—762年12月） [28]，字太白，号青莲居士
      [20]，祖籍陇西成纪（今甘肃省秦安县），出生于蜀郡绵州昌隆县（今四川省江油市青莲乡），一说出生于西域碎叶
      [29]。唐朝伟大的浪漫主义诗人，凉武昭王李暠九世孙 [16] [23]。为人爽朗大方，乐于交友，爱好饮酒作诗，名列“酒中八仙”
      [2]。曾经得到唐玄宗李隆基赏识，担任翰林供奉
      [126]，赐金放还，游历全国，先后迎娶宰相许圉师、宗楚客的孙女。唐肃宗李亨即位后，卷入永王之乱，流放夜郎，辗转到达当涂县令李阳冰家。上元二年，去世，时年六十二
      [16]。著有《李太白集》 [26]，代表作有《望庐山瀑布》《行路难》《蜀道难》《将进酒》《早发白帝城》《黄鹤楼送孟浩然之广陵》等
      [2]。李白所作词赋，就其开创意义及艺术成就而言，享有极为崇高的地位，后世誉为“诗仙”，与诗圣杜甫并称“李杜”。
  - text: >-
      李白，字太白，号青莲居士，又号“谪仙人”，祖籍陇西成纪（今甘肃省秦安县），唐代伟大的浪漫主义诗人，被誉为“诗仙”，与杜甫并称“李杜”。李白为人爽朗大方，爱饮酒作诗，喜交友。他深受黄老列庄思想影响，有“济苍生、安黎元”的政治抱负，但却仕途不顺，只做过一些从仕小官。天宝元年（公元742年），因好友举荐，李白被唐玄宗召见，供奉翰林，但他并未获得高位和实权，只是作为文学侍从的角色，因权贵的谗毁，于天宝三载（744年）被排挤出京，此后在江淮一带盘桓，历经磨难。安史之乱爆发后，李白因永王李璘谋反案被牵连而流放夜郎，途中写下《早发白帝城》。不久后又遇赦返回，继续过着飘荡四方的流浪生活。晚年李白投奔他的族叔、当时在当涂（今属安徽）当县令的李阳冰，不久即病逝，享年六十二岁。李白的诗歌创作具有极高的艺术成就。他的诗以抒情为主，善于从民歌、神话中汲取营养素材，构成其特有的瑰丽绚烂的色彩，是屈原以来积极浪漫主义诗歌的新高峰。他将叙事、议论、抒情三者融为一体，以气贯之，既而形成了雄奇飘逸的风格。他的诗歌既有大气磅礴、奔腾跳跃的气势和力量，又有壮丽奇伟的景象，其中也不乏清新明快的句子。李白的乐府、歌行及绝句成就为最高。其歌行，完全打破诗歌创作的一切固有格式，笔法多端，达到了极其逍遥自在、变幻莫测、摇曳多姿的神奇境界，充分体现了浪漫主义的风格。李白的绝句自然明快，飘逸潇洒，能以简洁明快的语言表达出无尽的情思。在盛唐诗人中，王维、孟浩然长于五绝，王昌龄等七绝写得很好，兼长五绝与七绝而且同臻极境的，只有李白一人。总的来说，李白是一位具有世界影响的伟大诗人，他的诗歌在中国文学史上占有重要地位，对后世产生了深远的影响。他的诗才横溢，被誉为“诗仙”，他的作品充满了浪漫主义的色彩，具有极高的艺术价值和历史意义。

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Model Details

Model Description

This model is an artificial intelligence generated text detection model trained using real human text and AI generated text (mainly including Erine-Bot 4.0, Qwen-Turbo 4.0 and ChatGPT 3.0 )Can effectively identify whether text is generated by artificial intelligence.

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  • Finetuned from model [optional]: [More Information Needed]

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Uses

Direct Use

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Bias, Risks, and Limitations

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Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

You could implement the model with the sample if you want to classify between AI-generated text and real-text.

from transformers import AutoTokenizer,AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("Juner/AI-generated-text-detection-pair")
model = AutoModelForSequenceClassification.from_pretrained("Juner/AI-generated-text-detection-pair")

# 对输入进行编码并获取模型输出
question = "你喜欢我吗？"
answer = "是的！我喜欢你！"
inputs = tokenizer(question+answer,padding =True,truncation=True,return_tensors="pt",max_length=512)
outputs = model(**inputs)

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Training Details

Training Data

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Training Procedure

Preprocessing [optional]

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Training Hyperparameters

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Speeds, Sizes, Times [optional]

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Evaluation

Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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Summary

Model Examination [optional]

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Software

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