基础
常见处理任务
情感分析 文本生成 阅读理解 机器翻译 特征提取 对话机器人等
相关库
核心库 分词器 数据集库 评估函数 微调 分布式训练 加速库 可视化部署库
pipeline
数据预处理 模型调用 结果后处理组成的流水线
支持很多任务
导入SUPPORTED_TASK可以查看支持的任务
from pprint import pprint
pprint(SUPPORTED_TASKS.keys())设置gpu 设置device 要已数字形式
查看pipeline参数 __call__
背后的实现
#参数
qa_pipe = pipeline("question-answering", model="uer/roberta-base-chinese-extractive-qa")
qa_pipe
QuestionAnsweringPipeline #任务
checkpoint = "google/owlvit-base-patch32"
detector = pipeline(model=checkpoint, task="zero-shot-object-detection")
tokenizer = AutoTokenizer.from_pretrained("uer/roberta-base-finetuned-dianping-chinese")
model = AutoModelForSequenceClassification.from_pretrained("uer/roberta-base-finetuned-dianping-chinese")
audio-classification {'impl': <class 'transformers.pipelines.audio_classification.AudioClassificationPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForAudioClassification'>,), 'default': {'model': {'pt': ('superb/wav2vec2-base-superb-ks', '372e048')}}, 'type': 'audio'}
automatic-speech-recognition {'impl': <class 'transformers.pipelines.automatic_speech_recognition.AutomaticSpeechRecognitionPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForCTC'>, <class 'transformers.models.auto.modeling_auto.AutoModelForSpeechSeq2Seq'>), 'default': {'model': {'pt': ('facebook/wav2vec2-base-960h', '22aad52')}}, 'type': 'multimodal'}
text-to-audio {'impl': <class 'transformers.pipelines.text_to_audio.TextToAudioPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForTextToWaveform'>, <class 'transformers.models.auto.modeling_auto.AutoModelForTextToSpectrogram'>), 'default': {'model': {'pt': ('suno/bark-small', '1dbd7a1')}}, 'type': 'text'}
feature-extraction {'impl': <class 'transformers.pipelines.feature_extraction.FeatureExtractionPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModel'>,), 'default': {'model': {'pt': ('distilbert/distilbert-base-cased', '6ea8117'), 'tf': ('distilbert/distilbert-base-cased', '6ea8117')}}, 'type': 'multimodal'}
text-classification {'impl': <class 'transformers.pipelines.text_classification.TextClassificationPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForSequenceClassification'>,), 'default': {'model': {'pt': ('distilbert/distilbert-base-uncased-finetuned-sst-2-english', '714eb0f'), 'tf': ('distilbert/distilbert-base-uncased-finetuned-sst-2-english', '714eb0f')}}, 'type': 'text'}
token-classification {'impl': <class 'transformers.pipelines.token_classification.TokenClassificationPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForTokenClassification'>,), 'default': {'model': {'pt': ('dbmdz/bert-large-cased-finetuned-conll03-english', '4c53496'), 'tf': ('dbmdz/bert-large-cased-finetuned-conll03-english', '4c53496')}}, 'type': 'text'}
question-answering {'impl': <class 'transformers.pipelines.question_answering.QuestionAnsweringPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForQuestionAnswering'>,), 'default': {'model': {'pt': ('distilbert/distilbert-base-cased-distilled-squad', '564e9b5'), 'tf': ('distilbert/distilbert-base-cased-distilled-squad', '564e9b5')}}, 'type': 'text'}
table-question-answering {'impl': <class 'transformers.pipelines.table_question_answering.TableQuestionAnsweringPipeline'>, 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForTableQuestionAnswering'>,), 'tf': (), 'default': {'model': {'pt': ('google/tapas-base-finetuned-wtq', 'e3dde19'), 'tf': ('google/tapas-base-finetuned-wtq', 'e3dde19')}}, 'type': 'text'}
visual-question-answering {'impl': <class 'transformers.pipelines.visual_question_answering.VisualQuestionAnsweringPipeline'>, 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForVisualQuestionAnswering'>,), 'tf': (), 'default': {'model': {'pt': ('dandelin/vilt-b32-finetuned-vqa', 'd0a1f6a')}}, 'type': 'multimodal'}
document-question-answering {'impl': <class 'transformers.pipelines.document_question_answering.DocumentQuestionAnsweringPipeline'>, 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForDocumentQuestionAnswering'>,), 'tf': (), 'default': {'model': {'pt': ('impira/layoutlm-document-qa', 'beed3c4')}}, 'type': 'multimodal'}
fill-mask {'impl': <class 'transformers.pipelines.fill_mask.FillMaskPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForMaskedLM'>,), 'default': {'model': {'pt': ('distilbert/distilroberta-base', 'fb53ab8'), 'tf': ('distilbert/distilroberta-base', 'fb53ab8')}}, 'type': 'text'}
summarization {'impl': <class 'transformers.pipelines.text2text_generation.SummarizationPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForSeq2SeqLM'>,), 'default': {'model': {'pt': ('sshleifer/distilbart-cnn-12-6', 'a4f8f3e'), 'tf': ('google-t5/t5-small', 'df1b051')}}, 'type': 'text'}
translation {'impl': <class 'transformers.pipelines.text2text_generation.TranslationPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForSeq2SeqLM'>,), 'default': {('en', 'fr'): {'model': {'pt': ('google-t5/t5-base', 'a9723ea'), 'tf': ('google-t5/t5-base', 'a9723ea')}}, ('en', 'de'): {'model': {'pt': ('google-t5/t5-base', 'a9723ea'), 'tf': ('google-t5/t5-base', 'a9723ea')}}, ('en', 'ro'): {'model': {'pt': ('google-t5/t5-base', 'a9723ea'), 'tf': ('google-t5/t5-base', 'a9723ea')}}}, 'type': 'text'}
text2text-generation {'impl': <class 'transformers.pipelines.text2text_generation.Text2TextGenerationPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForSeq2SeqLM'>,), 'default': {'model': {'pt': ('google-t5/t5-base', 'a9723ea'), 'tf': ('google-t5/t5-base', 'a9723ea')}}, 'type': 'text'}
text-generation {'impl': <class 'transformers.pipelines.text_generation.TextGenerationPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForCausalLM'>,), 'default': {'model': {'pt': ('openai-community/gpt2', '607a30d'), 'tf': ('openai-community/gpt2', '607a30d')}}, 'type': 'text'}
zero-shot-classification {'impl': <class 'transformers.pipelines.zero_shot_classification.ZeroShotClassificationPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForSequenceClassification'>,), 'default': {'model': {'pt': ('facebook/bart-large-mnli', 'd7645e1'), 'tf': ('FacebookAI/roberta-large-mnli', '2a8f12d')}, 'config': {'pt': ('facebook/bart-large-mnli', 'd7645e1'), 'tf': ('FacebookAI/roberta-large-mnli', '2a8f12d')}}, 'type': 'text'}
zero-shot-image-classification {'impl': <class 'transformers.pipelines.zero_shot_image_classification.ZeroShotImageClassificationPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForZeroShotImageClassification'>,), 'default': {'model': {'pt': ('openai/clip-vit-base-patch32', '3d74acf'), 'tf': ('openai/clip-vit-base-patch32', '3d74acf')}}, 'type': 'multimodal'}
zero-shot-audio-classification {'impl': <class 'transformers.pipelines.zero_shot_audio_classification.ZeroShotAudioClassificationPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModel'>,), 'default': {'model': {'pt': ('laion/clap-htsat-fused', 'cca9e28')}}, 'type': 'multimodal'}
image-classification {'impl': <class 'transformers.pipelines.image_classification.ImageClassificationPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForImageClassification'>,), 'default': {'model': {'pt': ('google/vit-base-patch16-224', '3f49326'), 'tf': ('google/vit-base-patch16-224', '3f49326')}}, 'type': 'image'}
image-feature-extraction {'impl': <class 'transformers.pipelines.image_feature_extraction.ImageFeatureExtractionPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModel'>,), 'default': {'model': {'pt': ('google/vit-base-patch16-224', '3f49326'), 'tf': ('google/vit-base-patch16-224', '3f49326')}}, 'type': 'image'}
image-segmentation {'impl': <class 'transformers.pipelines.image_segmentation.ImageSegmentationPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForImageSegmentation'>, <class 'transformers.models.auto.modeling_auto.AutoModelForSemanticSegmentation'>), 'default': {'model': {'pt': ('facebook/detr-resnet-50-panoptic', 'd53b52a')}}, 'type': 'multimodal'}
image-to-text {'impl': <class 'transformers.pipelines.image_to_text.ImageToTextPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForVision2Seq'>,), 'default': {'model': {'pt': ('ydshieh/vit-gpt2-coco-en', '5bebf1e'), 'tf': ('ydshieh/vit-gpt2-coco-en', '5bebf1e')}}, 'type': 'multimodal'}
image-text-to-text {'impl': <class 'transformers.pipelines.image_text_to_text.ImageTextToTextPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForImageTextToText'>,), 'default': {'model': {'pt': ('llava-hf/llava-onevision-qwen2-0.5b-ov-hf', '2c9ba3b')}}, 'type': 'multimodal'}
object-detection {'impl': <class 'transformers.pipelines.object_detection.ObjectDetectionPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForObjectDetection'>,), 'default': {'model': {'pt': ('facebook/detr-resnet-50', '1d5f47b')}}, 'type': 'multimodal'}
zero-shot-object-detection {'impl': <class 'transformers.pipelines.zero_shot_object_detection.ZeroShotObjectDetectionPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForZeroShotObjectDetection'>,), 'default': {'model': {'pt': ('google/owlvit-base-patch32', 'cbc355f')}}, 'type': 'multimodal'}
depth-estimation {'impl': <class 'transformers.pipelines.depth_estimation.DepthEstimationPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForDepthEstimation'>,), 'default': {'model': {'pt': ('Intel/dpt-large', 'bc15f29')}}, 'type': 'image'}
video-classification {'impl': <class 'transformers.pipelines.video_classification.VideoClassificationPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForVideoClassification'>,), 'default': {'model': {'pt': ('MCG-NJU/videomae-base-finetuned-kinetics', '488eb9a')}}, 'type': 'video'}
mask-generation {'impl': <class 'transformers.pipelines.mask_generation.MaskGenerationPipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForMaskGeneration'>,), 'default': {'model': {'pt': ('facebook/sam-vit-huge', '87aecf0')}}, 'type': 'multimodal'}
image-to-image {'impl': <class 'transformers.pipelines.image_to_image.ImageToImagePipeline'>, 'tf': (), 'pt': (<class 'transformers.models.auto.modeling_auto.AutoModelForImageToImage'>,), 'default': {'model': {'pt': ('caidas/swin2SR-classical-sr-x2-64', 'cee1c92')}}, 'type': 'image'}tokenizer
数据预处理 分词 构建词典 数据转化 填充与截断
# 从HuggingFace加载，输入模型名称，即可加载对于的分词器
tokenizer = AutoTokenizer.from_pretrained("uer/roberta-base-finetuned-dianping-chinese")
# tokenizer 保存到本地
tokenizer.save_pretrained("./roberta_tokenizer")
# 从本地加载tokenizer
tokenizer = AutoTokenizer.from_pretrained("./roberta_tokenizer/")
tokens = tokenizer.tokenize(sen)
tokenizer.vocab
# 将字符串转换为id序列，又称之为编码
ids = tokenizer.encode(sen, add_special_tokens=True)
# 将id序列转换为字符串，又称之为解码
str_sen = tokenizer.decode(ids, skip_special_tokens=False)