# few_shot_ner

此模型是基于 [uer/gpt2-chinese-cluecorpussmall](https://huggingface.co/uer/gpt2-chinese-cluecorpussmall) 在数据集 [qgyd2021/few_shot_ner_sft](https://huggingface.co/datasets/qgyd2021/few_shot_ner_sft) 上训练的.

可以在此处 [qgyd2021/gpt2_chat](https://huggingface.co/spaces/qgyd2021/gpt2_chat) 体验. 

基于此模型或数据集, 你可以: 

(1)小样本或零样本的实体识别. 

(2)用于实体识别数据集的辅助构建. 即当你在自己的数据集上进行了部分数据标注后, 可以与此数据集混合并训练模型, 之后用于数据自动标注/辅助标注.
{"language": ["zh", "en"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["qgyd2021/few_shot_ner_sft"], "pipeline_tag": "text-generation", "widget": [{"text": "\u5b9e\u4f53\u8bc6\u522b\u3002\n\n\u6ce8\u610f\uff1a\n- \u8bf7\u63d0\u53d6\u51fa \u201c\u59d3\u540d\u201d \u5b9e\u4f53\u3002\n\ntext\uff1a\u7530\u5174\uff0c\u66fe\u4efb\u5317\u4eac\u53cc\u9e64\u836f\u4e1a\u7ecf\u8425\u6709\u9650\u8d23\u4efb\u516c\u53f8\u8d22\u52a1\u603b\u76d1\u3001\u526f\u603b\u7ecf\u7406\uff1b\noutputs\uff1a[SEP]"}], "inference": {"parameters": {"max_new_tokens": 128, "top_p": 0.75, "temperature": 0.35, "repetition_penalty": 1.2, "eos_token_id": 102}}, "model-index": [{"name": "few_shot_ner", "results": []}]}
transformers pytorch gpt2 text-generation generated_from_trainer zh en dataset:qgyd2021/few_shot_ner_sft license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us