Many tasks have a pre-trained pipeline ready to go, in NLP but also in computer vision and speech. For example, we can easily extract detected objects in an image:>>> import requests >>> from PIL import Image >>> from transformers import pipeline # Download an image with cute cats >>...
computer-visiontransformersvitpose-estimationhuman-posevision-transformersvitpose UpdatedNov 21, 2023 Jupyter Notebook kahnchana/svt Star105 Official repository for "Self-Supervised Video Transformer" (CVPR'22) video-classificationself-supervised-learningvision-transformers ...
Multi-scale Vision Transformer (ViT) has emerged as a powerful backbone for computer vision tasks, while the self-attention computation in Transformer scales quadratically w.r.t. the input patch number. Thus, existing solutions commonly employ down-sampl
pipeline(管道)是huggingface transformers库中一种极简方式使用大模型推理的抽象,将所有大模型分为音频(Audio)、计算机视觉(Computer vision)、自然语言处理(NLP)、多模态(Multimodal)等4大类,28小类任务(tasks),共计覆盖32万个模型。 今天介绍Audio音频的第二篇,自动语音识别(automatic-speech-recognition),在huggingface...
pipeline(管道)是huggingface transformers库中一种极简方式使用大模型推理的抽象,将所有大模型分为语音(Audio)、计算机视觉(Computer vision)、自然语言处理(NLP)、多模态(Multimodal)等4大类,28小类任务(tasks)。共计覆盖32万个模型 本文对pipeline进行整体介绍,之后本专栏以每个task为主题,分别介绍各种task使用方法。
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CvT(来自 Microsoft) 伴随论文CvT: Introducing Convolutions to Vision Transformers由 Haiping Wu, Bin Xiao, Noel Codella, Mengchen Liu, Xiyang Dai, Lu Yuan, Lei Zhang 发布。 Data2Vec(来自 Facebook) 伴随论文Data2Vec: A General Framework for Self-supervised Learning in Speech, Vision and Language...
VisualBERT(来自 UCLA NLP) 伴随论文VisualBERT: A Simple and Performant Baseline for Vision and Language由 Liunian Harold Li, Mark Yatskar, Da Yin, Cho-Jui Hsieh, Kai-Wei Chang 发布。 Wav2Vec2(来自 Facebook AI) 伴随论文wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Repres...
Vision Transformers (ViTs), which made a splash in the field of computer vision (CV), have shaken the dominance of convolutional neural networks (CNNs). However, in the process of industrializing ViTs, backdoor attacks have brought severe challenges to security. T...
from_pretrained("facebook/wav2vec2-base") audio_input = [dataset[0]["audio"]["array"]] feature_extractor(audio_input, sampling_rate=16000) # 创建一个函数来预处理数据集,使音频样本的长度相同。指定最大样本长度,特征提取器将填充或截断序列以匹配它: def preprocess_function(examples): audio_...