训练:CPU、GPU、GPU+混合精度、Torch/XLA TPU。 https://github.com/huggingface/transformers/releases/tag/v3.0.0
pythonnlpmachine-learningnatural-language-processingdeep-learningtensorflowpytorchtransformerspeech-recognitionseq2seqflaxpretrained-modelslanguage-modelsnlp-librarylanguage-modelhacktoberfestbertjaxpytorch-transformersmodel-hub UpdatedNov 13, 2024 Python labmlai/annotated_deep_learning_paper_implementations ...
https://github.com/huggingface/transformers/releases/tag/v3.0.0
Transformers is more than a toolkit to use pretrained models: it's a community of projects built around it and the Hugging Face Hub. We want Transformers to enable developers, researchers, students, professors, engineers, and anyone else to build their dream projects. In order to celebrate the...
针对PyTorch增加了推理和训练: 推理:CPU, CPU + torch, GPU, GPU + torch, GPU + 混合精度, Torch/XLA TPU 训练:CPU、GPU、GPU+混合精度、Torch/XLA TPU。 更多内容,请移步Transformer的G站页面: https://github.com/huggingface/transformers/releases/tag/v3.0.0...
推理:CPU, CPU + torchscript, GPU, GPU + torchscript, GPU + 混合精度, Torch/XLA TPU 训练:CPU、GPU、GPU+混合精度、Torch/XLA TPU。 更多内容,请移步Transformer的G站页面: https://github.com/huggingface/transformers/releases/tag/v3.0.0
https://huggingface.co/transformers/master/preprocessing.html。 下面我们来看看这些显著的变化: 现在可以截断一个模型的最大输入长度,同时填充一个批次中最长的序列。 填充和截断被解耦,更容易控制。 它可以pad到预定义长度的倍数例如8,可以为最新的NVIDIA GPU(V100)带来显著的速度提升。
最后是蒸馏，采用的流程出自 Facebook AI 和索邦大学的论文《Training data-efficient image transformers & distillation through attention》论文地址：https://arxiv.org/pdf/2012.12877.pdf 从 ResNet50（或任何教师网络）蒸馏到 vision transformer 的代码如下：import torchfrom torchvision.models import resnet50...
https://github.com/huggingface/transformers 作者系网易新闻·网易号“各有态度”签约作者 —完— 如何关注、学习、用好人工智能? 每个工作日,量子位AI内参精选全球科技和研究最新动态,汇总新技术、新产品和新应用,梳理当日最热行业趋势和政策,搜索有价值的论文、教程、研究等。
all of them have slightly different APIs, requiring slightly different usage. JSTransformer unifies them into one standardized API. Code written for one transformer will work with any other transformer. There areover 100 transformers, ranging from Markdown parsers to template engines to code compilers...