提交 96613910 编写于 作者: 悟、's avatar 悟、 提交者: zengshao0622

fix name

上级 6b759405
......@@ -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
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