预训练模型与数据集下载链接
Coggle 阿水·
使用方法直接复制链接下载或者wget下载，链接在服务器直接下载。
部分文件链接是http链接，请放心下载。
seaborn-data
https://github.com/mwaskom/seaborn-data
百度云链接: https://pan.baidu.com/s/1Uvw6gKe9XPwOW7e-JeVMIg?pwd=6666 提取码: 6666
NLTK
http://www.nltk.org/nltk_data/
百度云链接: https://pan.baidu.com/s/1OZESIEUwWUE1hbKbgFvxlQ?pwd=6666 提取码: 6666
- nltk_data/abc.zip
- nltk_data/alpino.zip
- nltk_data/averaged_perceptron_tagger.zip
- nltk_data/averaged_perceptron_tagger_ru.zip
- nltk_data/basque_grammars.zip
- nltk_data/biocreative_ppi.zip
- nltk_data/bllip_wsj_no_aux.zip
- nltk_data/book_grammars.zip
- nltk_data/brown.zip
- nltk_data/brown_tei.zip
- nltk_data/cess_cat.zip
- nltk_data/cess_esp.zip
- nltk_data/chat80.zip
- nltk_data/city_database.zip
- nltk_data/cmudict.zip
- nltk_data/comparative_sentences.zip
- nltk_data/comtrans.zip
- nltk_data/conll2000.zip
- nltk_data/conll2002.zip
- nltk_data/conll2007.zip
- nltk_data/crubadan.zip
- nltk_data/dependency_treebank.zip
- nltk_data/dolch.zip
- nltk_data/europarl_raw.zip
- nltk_data/floresta.zip
- nltk_data/gazetteers.zip
- nltk_data/genesis.zip
- nltk_data/gutenberg.zip
- nltk_data/ieer.zip
- nltk_data/inaugural.zip
- nltk_data/indian.zip
- nltk_data/jeita.zip
- nltk_data/kimmo.zip
- nltk_data/knbc.zip
- nltk_data/large_grammars.zip
- nltk_data/mac_morpho.zip
- nltk_data/machado.zip
- nltk_data/masc_tagged.zip
- nltk_data/maxent_ne_chunker.zip
- nltk_data/maxent_treebank_pos_tagger.zip
- nltk_data/moses_sample.zip
- nltk_data/movie_reviews.zip
- nltk_data/mte_teip5.zip
- nltk_data/mwa_ppdb.zip
- nltk_data/names.zip
- nltk_data/nombank.1.0.zip
- nltk_data/nonbreaking_prefixes.zip
- nltk_data/nps_chat.zip
- nltk_data/omw.zip
- nltk_data/opinion_lexicon.zip
- nltk_data/panlex_swadesh.zip
- nltk_data/paradigms.zip
- nltk_data/pe08.zip
- nltk_data/perluniprops.zip
- nltk_data/pil.zip
- nltk_data/pl196x.zip
- nltk_data/porter_test.zip
- nltk_data/ppattach.zip
- nltk_data/problem_reports.zip
- nltk_data/product_reviews_1.zip
- nltk_data/product_reviews_2.zip
- nltk_data/propbank.zip
- nltk_data/pros_cons.zip
- nltk_data/ptb.zip
- nltk_data/punkt.zip
- nltk_data/qc.zip
- nltk_data/reuters.zip
- nltk_data/rslp.zip
- nltk_data/rte.zip
- nltk_data/sample_grammars.zip
- nltk_data/semcor.zip
- nltk_data/senseval.zip
- nltk_data/sentence_polarity.zip
- nltk_data/sentiwordnet.zip
- nltk_data/shakespeare.zip
- nltk_data/sinica_treebank.zip
- nltk_data/smultron.zip
- nltk_data/snowball_data.zip
- nltk_data/spanish_grammars.zip
- nltk_data/state_union.zip
- nltk_data/stopwords.zip
- nltk_data/subjectivity.zip
- nltk_data/swadesh.zip
- nltk_data/switchboard.zip
- nltk_data/tagsets.zip
- nltk_data/timit.zip
- nltk_data/toolbox.zip
- nltk_data/treebank.zip
- nltk_data/twitter_samples.zip
- nltk_data/udhr.zip
- nltk_data/udhr2.zip
- nltk_data/unicode_samples.zip
- nltk_data/universal_tagset.zip
- nltk_data/universal_treebanks_v20.zip
- nltk_data/vader_lexicon.zip
- nltk_data/verbnet.zip
- nltk_data/verbnet3.zip
- nltk_data/webtext.zip
- nltk_data/wmt15_eval.zip
- nltk_data/word2vec_sample.zip
- nltk_data/wordnet.zip
- nltk_data/wordnet_ic.zip
- nltk_data/words.zip
- nltk_data/ycoe.zip
keras
https://github.com/fchollet/deep-learning-models/releases/
- densenet121_weights_tf_dim_ordering_tf_kernels.h5
- densenet121_weights_tf_dim_ordering_tf_kernels_notop.h5
- densenet169_weights_tf_dim_ordering_tf_kernels.h5
- densenet169_weights_tf_dim_ordering_tf_kernels_notop.h5
- densenet201_weights_tf_dim_ordering_tf_kernels.h5
- densenet201_weights_tf_dim_ordering_tf_kernels_notop.h5
- NASNet-large-no-top.h5
- NASNet-large.h5
- NASNet-mobile-no-top.h5
- NASNet-mobile.h5
- inception_resnet_v2_weights_tf_dim_ordering_tf_kernels.h5
- inception_resnet_v2_weights_tf_dim_ordering_tf_kernels_notop.h5
- mobilenet_1_0_128_tf.h5
- mobilenet_1_0_128_tf_no_top.h5
- mobilenet_1_0_160_tf.h5
- mobilenet_1_0_160_tf_no_top.h5
- mobilenet_1_0_192_tf.h5
- mobilenet_1_0_192_tf_no_top.h5
- mobilenet_1_0_224_tf.h5
- mobilenet_1_0_224_tf_no_top.h5
- mobilenet_2_5_128_tf.h5
- mobilenet_2_5_128_tf_no_top.h5
- mobilenet_2_5_160_tf.h5
- mobilenet_2_5_160_tf_no_top.h5
- mobilenet_2_5_192_tf.h5
- mobilenet_2_5_192_tf_no_top.h5
- mobilenet_2_5_224_tf.h5
- mobilenet_2_5_224_tf_no_top.h5
- mobilenet_5_0_128_tf.h5
- mobilenet_5_0_128_tf_no_top.h5
- mobilenet_5_0_160_tf.h5
- mobilenet_5_0_160_tf_no_top.h5
- mobilenet_5_0_192_tf.h5
- mobilenet_5_0_192_tf_no_top.h5
- mobilenet_5_0_224_tf.h5
- mobilenet_5_0_224_tf_no_top.h5
- mobilenet_7_5_128_tf.h5
- mobilenet_7_5_128_tf_no_top.h5
- mobilenet_7_5_160_tf.h5
- mobilenet_7_5_160_tf_no_top.h5
- mobilenet_7_5_192_tf.h5
- mobilenet_7_5_192_tf_no_top.h5
- mobilenet_7_5_224_tf.h5
- mobilenet_7_5_224_tf_no_top.h5
- inception_v3_weights_tf_dim_ordering_tf_kernels.h5
- inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5
- xception_weights_tf_dim_ordering_tf_kernels.h5
- xception_weights_tf_dim_ordering_tf_kernels_notop.h5
- music_tagger_crnn_weights_tf_kernels_tf_dim_ordering.h5
- music_tagger_crnn_weights_tf_kernels_th_dim_ordering.h5
- inception_v3_weights_tf_dim_ordering_tf_kernels.h5
- inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5
- inception_v3_weights_th_dim_ordering_th_kernels.h5
- inception_v3_weights_th_dim_ordering_th_kernels_notop.h5
- resnet50_weights_tf_dim_ordering_tf_kernels.h5
- resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5
- resnet50_weights_th_dim_ordering_th_kernels.h5
- resnet50_weights_th_dim_ordering_th_kernels_notop.h5
- resnet50_weights_tf_dim_ordering_tf_kernels.h5
- resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5
- resnet50_weights_th_dim_ordering_th_kernels.h5
- resnet50_weights_th_dim_ordering_th_kernels_notop.h5
- vgg16_weights_tf_dim_ordering_tf_kernels.h5
- vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5
- vgg16_weights_th_dim_ordering_th_kernels.h5
- vgg16_weights_th_dim_ordering_th_kernels_notop.h5
- vgg19_weights_tf_dim_ordering_tf_kernels.h5
- vgg19_weights_tf_dim_ordering_tf_kernels_notop.h5
torchvision
https://github.com/pytorch/vision
百度云链接: https://pan.baidu.com/s/1NA4XOUbIMMUUjgZFVbzAyQ?pwd=6666 提取码: 6666
timm
https://github.com/rwightman/pytorch-image-models
百度云链接: https://pan.baidu.com/s/1FXNn865dBd-O4HLMY9H_YQ?pwd=6666 提取码: 6666
HuggingFace Models
百度云链接: https://pan.baidu.com/s/1Gqt5soUpxAKtkhZBRCRquQ?pwd=tele 提取码:tele 复制这段内容后打开百度网盘手机App，操作更方便哦
pretrained-models.pytorch
https://github.com/Cadene/pretrained-models.pytorch
EfficientNet-PyTorch
https://github.com/lukemelas/EfficientNet-PyTorch
tensorflow-models
https://github.com/tensorflow/models
darknet
ultralytics-yolov5
https://github.com/ultralytics/yolov5/
- V6.0
- ultralytics/yolov5/v6.0/yolov5l-fp16-320.tflite
- ultralytics/yolov5/v6.0/yolov5l.mlmodel
- ultralytics/yolov5/v6.0/yolov5l.onnx
- ultralytics/yolov5/v6.0/yolov5l.pt
- ultralytics/yolov5/v6.0/yolov5l6.pt
- ultralytics/yolov5/v6.0/yolov5m-fp16-320.tflite
- ultralytics/yolov5/v6.0/yolov5m.mlmodel
- ultralytics/yolov5/v6.0/yolov5m.onnx
- ultralytics/yolov5/v6.0/yolov5m.pt
- ultralytics/yolov5/v6.0/yolov5m6.pt
- ultralytics/yolov5/v6.0/yolov5m_Objects365.pt
- ultralytics/yolov5/v6.0/yolov5n-fp16-320.tflite
- ultralytics/yolov5/v6.0/yolov5n.mlmodel
- ultralytics/yolov5/v6.0/yolov5n.onnx
- ultralytics/yolov5/v6.0/yolov5n.pt
- ultralytics/yolov5/v6.0/yolov5n6.pt
- ultralytics/yolov5/v6.0/yolov5s-fp16-256x320.tflite
- ultralytics/yolov5/v6.0/yolov5s-fp16-320.tflite
- ultralytics/yolov5/v6.0/yolov5s-fp16-320x192.tflite
- ultralytics/yolov5/v6.0/yolov5s.mlmodel
- ultralytics/yolov5/v6.0/yolov5s.onnx
- ultralytics/yolov5/v6.0/yolov5s.pt
- ultralytics/yolov5/v6.0/yolov5s6.pt
- ultralytics/yolov5/v6.0/yolov5x-fp16-320.tflite
- ultralytics/yolov5/v6.0/yolov5x.mlmodel
- ultralytics/yolov5/v6.0/yolov5x.onnx
- ultralytics/yolov5/v6.0/yolov5x.pt
- ultralytics/yolov5/v6.0/yolov5x6.pt
mmdetection
https://github.com/open-mmlab/mmdetection
insightface
https://github.com/deepinsight/insightface
- model-MobileFaceNet-arcface-ms1m-refine-v1.zip
- model-r34-arcface-ms1m-refine-v1.zip
- model-r50-arcface-ms1m-refine-v1.zip
- model-r100-arcface-ms1m-refine-v2.zip
- ssh-model-final.zip
bert
- https://github.com/google-research/bert
- https://github.com/brightmart/roberta_zh
- https://github.com/ymcui/Chinese-BERT-wwm
- https://github.com/google-research/albert
- https://github.com/lonePatient/NeZha_Chinese_PyTorch
- https://github.com/allenai/scibert
- https://github.com/dbiir/UER-py/