From 966139108d41a45d72ae8bf4b1001e69e42231d6 Mon Sep 17 00:00:00 2001 From: zengshao0622 Date: Tue, 7 Feb 2023 06:31:59 +0000 Subject: [PATCH] fix name --- docs/zh_CN/models/ImageNet1k/FoundationViT.md | 32 +++++++++---------- 1 file changed, 16 insertions(+), 16 deletions(-) diff --git a/docs/zh_CN/models/ImageNet1k/FoundationViT.md b/docs/zh_CN/models/ImageNet1k/FoundationViT.md index 1e308690..26e00887 100644 --- a/docs/zh_CN/models/ImageNet1k/FoundationViT.md +++ b/docs/zh_CN/models/ImageNet1k/FoundationViT.md @@ -13,14 +13,14 @@ ## 2. 使用说明 -以模型`CLIP_base_patch16_224`为例，使用该模型以及对应的预训练权重进行特征提取的代码如下： +以模型`CLIP_vit_base_patch16_224`为例，使用该模型以及对应的预训练权重进行特征提取的代码如下： ```python from ppcls.utils import config from ppcls.arch import build_model import paddle -pretrained = './paddle_weights/CAE_base_patch16_224.pdparams' # path to pretrained weight -cfg = {"Arch": {"name": "CLIP_base_patch16_224"}} +pretrained = './paddle_weights/CLIP_vit_base_patch16_224.pdparams' # path to pretrained weight +cfg = {"Arch": {"name": "CLIP_vit_base_patch16_224"}} model = build_model(cfg, mode="train") model.set_state_dict(paddle.load(pretrained)) inputs = paddle.randn((1,3,224,224)) # create input @@ -33,19 +33,19 @@ output = model(inputs) # the output of model embeding | 系列 | 模型 | 模型大小 | embedding_size | 预训练数据集 | | :----: | :----------------------: | :------: | :------------: | :----------------------------------------------: | -| CLIP | CLIP_base_patch16_224 | 85M | 768 | WIT | -| CLIP | CLIP_base_patch32_224 | 87M | 768 | WIT | -| CLIP | CLIP_large_patch14_224 | 302M | 1024 | WIT | -| CLIP | CLIP_large_patch14_336 | 302M | 1024 | WIT | -| BEiTv2 | BEiTv2_base_patch16_224 | 85M | 768 | ImageNet-1k | -| BEiTv2 | BEiTv2_large_patch16_224 | 303M | 1024 | ImageNet-1k | -| MoCoV3 | MoCoV3_small | 21M | 384 | ImageNet-1k | -| MoCoV3 | MoCoV3_base | 85M | 768 | ImageNet-1k | -| MAE | MAE_base_patch16 | 85M | 768 | ImageNet-1k | -| MAE | MAE_large_patch16 | 303M | 1024 | ImageNet-1k | -| MAE | MAE_huge_patch14 | 630M | 1280 | ImageNet-1k | -| EVA | EVA_huge_patch14 | 1010M | 1408 | ImageNet-21k, CC12M, CC2M, Object365,COCO, ADE | -| CAE | CAE_base_patch16_224 | 85M | 768 | ImageNet-1k | +| CLIP | CLIP_vit_base_patch16_224 | 85M | 768 | WIT | +| CLIP | CLIP_vit_base_patch32_224 | 87M | 768 | WIT | +| CLIP | CLIP_vit_large_patch14_224 | 302M | 1024 | WIT | +| CLIP | CLIP_vit_large_patch14_336 | 302M | 1024 | WIT | +| BEiTv2 | BEiTv2_vit_base_patch16_224 | 85M | 768 | ImageNet-1k | +| BEiTv2 | BEiTv2_vit_large_patch16_224 | 303M | 1024 | ImageNet-1k | +| MoCoV3 | MoCoV3_vit_small | 21M | 384 | ImageNet-1k | +| MoCoV3 | MoCoV3_vit_base | 85M | 768 | ImageNet-1k | +| MAE | MAE_vit_base_patch16 | 85M | 768 | ImageNet-1k | +| MAE | MAE_vit_large_patch16 | 303M | 1024 | ImageNet-1k | +| MAE | MAE_vit_huge_patch14 | 630M | 1280 | ImageNet-1k | +| EVA | EVA_vit_huge_patch14 | 1010M | 1408 | ImageNet-21k, CC12M, CC2M, Object365,COCO, ADE | +| CAE | CAE_vit_base_patch16_224 | 85M | 768 | ImageNet-1k | ## 4. 参考文献 -- GitLab