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b594d2c6
编写于
11月 10, 2021
作者:
H
huangjianhui
提交者：
GitHub
11月 10, 2021
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# Model Zoo
本页面展示了Paddle Serving目前支持的预训练模型以及下载链接
若您想为Paddle Serving提供新的模型，可通过
[
pull requese
](
https://github.com/PaddlePaddle/Serving/pulls
)
提交PR
*特别感谢[PadddlePaddle 全链条](https://www.paddlepaddle.org.cn/wholechain)以及[PaddleHub](https://www.paddlepaddle.org.cn/hub)为Paddle Serving提供的部分预训练模型*
| Model | Type | Dataset | Size | Download | Sample Input| Model mode |
| --- | --- | --- | --- | --- | --- | --- |
| ResNet V2 50 | PaddleClas | ImageNet | 90.78 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/paddle_hub_models/image/ImageClassification/resnet_v2_50_imagenet.tar.gz
)
|
[
daisy.jpg
](
../examples/PaddleClas/resnet_v2_50/daisy.jpg
)
|Eager|
| MobileNet_v2 | PaddleClas | ImageNet | 8.06 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/paddle_hub_models/image/ImageClassification/mobilenet_v2_imagenet.tar.gz
)
|
[
daisy.jpg
](
../examples/PaddleClas/mobilenet/daisy.jpg
)
|Eager|
| Bert | PaddleNLP | zhwiki | 361.96 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/paddle_hub_models/text/SemanticModel/bert_chinese_L-12_H-768_A-12.tar.gz
)
|
[
data-c.txt
](
../examples/PaddleNLP/data-c.txt
)
|Eager|
| Senta | PaddleNLP | Baidu | 578.37 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/paddle_hub_models/text/SentimentAnalysis/senta_bilstm.tar.gz
)
| |Eager|
| Lac | PaddleNLP | Baidu | 11.38 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/paddle_hub_models/text/LexicalAnalysis/lac.tar.gz
)
| |Eager|
| Criteo Ctr | PaddleRec | | 36.72 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/criteo_ctr_example/criteo_ctr_demo_model.tar.gz
)
|
[
ctr_data.tar.gz
](
https://paddle-serving.bj.bcebos.com/data/ctr_prediction/ctr_data.tar.gz
)
|Eager|
| Criteo Ctr With Cube | PaddleRec | | 41.68 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/unittest/ctr_cube_unittest.tar.gz
)
|
[
ctr_data.tar.gz
](
https://paddle-serving.bj.bcebos.com/data/ctr_prediction/ctr_data.tar.gz
)
|Eager|
| BlazeFace | PaddleDetection | WIDER-FACE | 1.40 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/paddle_hub_models/image/ObjectDetection/blazeface.tar.gz
)
|
[
test.jpg
](
../examples/PaddleDetection/blazeface
)
|Eager|
| Cascade RCNN | PaddleDetection | ImageNet | 255.58 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/pddet_demo/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco_serving.tar.gz
)
|
[
000000570688.jpg
](
../examples/PaddleDetection/cascade_rcnn/000000570688.jpg
)
|Eager|
| Yolov4 | PaddleDetection | ImageNet | 228.38 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/paddle_hub_models/image/ObjectDetection/yolov4.tar.gz
)
|
[
000000570688.jpg
](
../examples/PaddleDetection/yolov4/000000570688.jpg
)
|Eager|
| Faster RCNN HRNetv2p w18 1x | PaddleDetection | ImageNet | 97.57 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/pddet_demo/faster_rcnn_hrnetv2p_w18_1x.tar.gz
)
|
[
000000570688.jpg
](
../examples/PaddleDetection/faster_rcnn_hrnetv2p_w18_1x/000000570688.jpg
)
|Eager|
| Fcos DCN R50 FPN 1x coco | PaddleDetection | ImageNet | 119.55 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/fcos_dcn_r50_fpn_1x_coco.tar
)
|
[
000000570688.jpg
](
../examples/PaddleDetection/fcos_dcn_r50_fpn_1x_coco/000000570688.jpg
)
|Eager|
| SSD VGG16 300 240e VOC | PaddleDetection | ImageNet | 93.16 MB |
[
.tar
](
https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/ssd_vgg16_300_240e_voc.tar
)
|
[
000000014439.jpg
](
../examples/PaddleDetection/ssd_vgg16_300_240e_voc/000000014439.jpg
)
|Torchscripted |
| Yolov3 DarkNet53 270e coco | PaddleDetection | ImageNet | 219.71 MB |
[
.tar
](
https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/yolov3_darknet53_270e_coco.tar
)
|
[
000000570688.jpg
](
../examples/PaddleDetection/yolov3_darknet53_270e_coco/000000570688.jpg
)
|Torchscripted |
| Faster RCNN r50 Fpn 1x coco | PaddleDetection | ImageNet | 148.12 MB |
[
.tar
](
https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/faster_rcnn_r50_fpn_1x_coco.tar
)
|
[
000000570688.jpg
](
../examples/PaddleDetection/faster_rcnn_r50_fpn_1x_coco/000000570688.jpg
)
|Torchscripted |
| PPYolo r50vd DCN 1x coco | PaddleDetection | ImageNet | 167.03 MB |
[
.tar
](
https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/ppyolo_r50vd_dcn_1x_coco.tar
)
|
[
000000570688.jpg
](
../examples/PaddleDetection/ppyolo_r50vd_dcn_1x_coco/000000570688.jpg
)
|Torchscripted |
| TTFNet DarkNet53 1x coco | PaddleDetection | ImageNet | 162.19 MB |
[
.tar
](
https://paddle-serving.bj.bcebos.com/pddet_demo/ttfnet_darknet53_1x_coco.tar
)
|
[
000000570688.jpg
](
../examples/PaddleDetection/ttfnet_darknet53_1x_coco/000000570688.jpg
)
|Torchscripted |
| OCR REC | PaddleOCR | | 3.80 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/paddle_hub_models/image/OCR/ocr_rec.tar.gz
)
|
[
test_imgs.tar
](
https://paddle-serving.bj.bcebos.com/ocr/test_imgs.tar
)
|Torchscripted |
| Deeplabv3/ | PaddleSeg | Baidu | 146.97 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/paddle_hub_models/image/ImageSegmentation/deeplabv3.tar.gz
)
|
[
N0060.jpg
](
../examples/PaddleSeg/deeplabv3/N0060.jpg
)
|Torchscripted |
| UNet For Image Seg | PaddleSeg | | 47.69 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/paddle_hub_models/image/ImageSegmentation/unet.tar.gz
)
|
[
N0060.jpg
](
../examples/PaddleSeg/unet_for_image_seg/N0060.jpg
)
|Torchscripted |
Refer
[
example
](
../examples
)
for more details on above models.
doc/model_zoo.md
已删除
100644 → 0
浏览文件 @
06263404
# Model Zoo
本页面展示了Paddle Serving目前支持的预训练模型以及下载链接
若您想为Paddle Serving提供新的模型，可通过
[
pull requese
](
https://github.com/PaddlePaddle/Serving/pulls
)
提交PR
*特别感谢[PadddlePaddle 全链条](https://www.paddlepaddle.org.cn/wholechain)以及[PaddleHub](https://www.paddlepaddle.org.cn/hub)为Paddle Serving提供的部分预训练模型*
| Model | Type | Dataset | Size | Download | Sample Input| Model mode |
| --- | --- | --- | --- | --- | --- | --- |
| ResNet_V2_50 | PaddleClas | ImageNet | 90.78 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/paddle_hub_models/image/ImageClassification/resnet_v2_50_imagenet.tar.gz
)
|
[
daisy.jpg
](
../examples/PaddleClas/resnet_v2_50/daisy.jpg
)
|Eager|
| MobileNet_v2 | PaddleClas | ImageNet | 8.06 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/paddle_hub_models/image/ImageClassification/mobilenet_v2_imagenet.tar.gz
)
|
[
daisy.jpg
](
../examples/PaddleClas/mobilenet/daisy.jpg
)
|Eager|
| Bert | PaddleNLP | zhwiki | 361.96 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/paddle_hub_models/text/SemanticModel/bert_chinese_L-12_H-768_A-12.tar.gz
)
|
[
data-c.txt
](
../examples/PaddleNLP/data-c.txt
)
|Eager|
| Senta | PaddleNLP | Baidu | 578.37 MB |
[
.tar.gz
](
https://paddle-serving.bj.bcebos.com/paddle_hub_models/text/SentimentAnalysis/senta_bilstm.tar.gz
)
| |Eager|
| Squeezenet 1_1 | Image Classification | ImageNet | 4.4 MB |
[
.mar
](
https://torchserve.pytorch.org/mar_files/squeezenet1_1.mar
)
|
[
kitten.jpg
](
../examples/image_classifier/kitten.jpg
)
|Eager|
| MNIST digit classifier | Image Classification | MNIST | 4.3 MB |
[
.mar
](
https://torchserve.pytorch.org/mar_files/mnist_v2.mar
)
|
[
0.png
](
../examples/image_classifier/mnist/test_data/0.png
)
|Eager|
| Resnet 152 |Image Classification | ImageNet | 214 MB |
[
.mar
](
https://torchserve.pytorch.org/mar_files/resnet-152-batch_v2.mar
)
|
[
kitten.jpg
](
../examples/image_classifier/kitten.jpg
)
|Eager|
| Faster RCNN | Object Detection | COCO | 148 MB |
[
.mar
](
https://torchserve.pytorch.org/mar_files/fastrcnn.mar
)
|
[
persons.jpg
](
../examples/object_detector/persons.jpg
)
|Eager|
| MASK RCNN | Object Detection | COCO | 158 MB |
[
.mar
](
https://torchserve.pytorch.org/mar_files/maskrcnn.mar
)
|
[
persons.jpg
](
../examples/object_detector/persons.jpg
)
|Eager|
| Text classifier | Text Classification | AG_NEWS | 169 MB |
[
.mar
](
https://torchserve.pytorch.org/mar_files/my_text_classifier_v4.mar
)
|
[
sample_text.txt
](
../examples/text_classification/sample_text.txt
)
|Eager|
| FCN ResNet 101 | Image Segmentation | COCO | 193 MB |
[
.mar
](
https://torchserve.pytorch.org/mar_files/fcn_resnet_101.mar
)
|
[
persons.jpg
](
../examples/image_segmenter/persons.jpg
)
|Eager|
| DeepLabV3 ResNet 101 | Image Segmentation | COCO | 217 MB |
[
.mar
](
https://torchserve.pytorch.org/mar_files/deeplabv3_resnet_101_eager.mar
)
|
[
persons.jpg
](
https://github.com/pytorch/serve/blob/master/examples/image_segmenter/persons.jpg
)
|Eager|
| AlexNet Scripted | Image Classification | ImageNet | 216 MB |
[
.mar
](
https://torchserve.pytorch.org/mar_files/alexnet_scripted.mar
)
|
[
kitten.jpg
](
../examples/image_classifier/kitten.jpg
)
|Torchscripted |
| Densenet161 Scripted| Image Classification | ImageNet | 105 MB |
[
.mar
](
https://torchserve.pytorch.org/mar_files/densenet161_scripted.mar
)
|
[
kitten.jpg
](
../examples/image_classifier/kitten.jpg
)
|Torchscripted |
| Resnet18 Scripted| Image Classification | ImageNet | 42 MB |
[
.mar
](
https://torchserve.pytorch.org/mar_files/resnet-18_scripted.mar
)
|
[
kitten.jpg
](
../examples/image_classifier/kitten.jpg
)
|Torchscripted |
| VGG16 Scripted| Image Classification | ImageNet | 489 MB |
[
.mar
](
https://torchserve.pytorch.org/mar_files/vgg16_scripted.mar
)
|
[
kitten.jpg
](
../examples/image_classifier/kitten.jpg
)
|Torchscripted |
| Squeezenet 1_1 Scripted | Image Classification | ImageNet | 4.4 MB |
[
.mar
](
https://torchserve.pytorch.org/mar_files/squeezenet1_1_scripted.mar
)
|
[
kitten.jpg
](
../examples/image_classifier/kitten.jpg
)
|Torchscripted |
| MNIST digit classifier Scripted | Image Classification | MNIST | 4.3 MB |
[
.mar
](
https://torchserve.pytorch.org/mar_files/mnist_scripted_v2.mar
)
|
[
0.png
](
../examples/image_classifier/mnist/test_data/0.png
)
|Torchscripted |
| Resnet 152 Scripted |Image Classification | ImageNet | 215 MB |
[
.mar
](
https://torchserve.pytorch.org/mar_files/resnet-152-scripted_v2.mar
)
|
[
kitten.jpg
](
../examples/image_classifier/kitten.jpg
)
|Torchscripted |
| Text classifier Scripted | Text Classification | AG_NEWS | 169 MB |
[
.mar
](
https://torchserve.pytorch.org/mar_files/my_text_classifier_scripted_v3.mar
)
|
[
sample_text.txt
](
../examples/text_classification/sample_text.txt
)
|Torchscripted |
| FCN ResNet 101 Scripted | Image Segmentation | COCO | 193 MB |
[
.mar
](
https://torchserve.pytorch.org/mar_files/fcn_resnet_101_scripted.mar
)
|
[
persons.jpg
](
../examples/image_segmenter/persons.jpg
)
|Torchscripted |
| DeepLabV3 ResNet 101 Scripted | Image Segmentation | COCO | 217 MB |
[
.mar
](
https://torchserve.pytorch.org/mar_files/deeplabv3_resnet_101_scripted.mar
)
|
[
persons.jpg
](
https://github.com/pytorch/serve/blob/master/examples/image_segmenter/persons.jpg
)
|Torchscripted |
Refer
[
example
](
../examples
)
for more details on above models.
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