Add model
Browse files- README.md +308 -0
- config.json +35 -0
- pytorch_model.bin +3 -0
README.md
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| 1 |
+
---
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| 2 |
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tags:
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- image-classification
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- timm
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library_tag: timm
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license: apache-2.0
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datasets:
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- imagenet-1k
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- laion-2b
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---
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# Model card for convnext_large_mlp.clip_laion2b_augreg_ft_in1k
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A ConvNeXt image classification model. CLIP image tower weights pretrained in [OpenCLIP](https://github.com/mlfoundations/open_clip) on LAION and fine-tuned on ImageNet-1k in `timm` by Ross Wightman.
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Please see related OpenCLIP model cards for more details on pretrain:
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* https://huggingface.co/laion/CLIP-convnext_large_d.laion2B-s26B-b102K-augreg
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* https://huggingface.co/laion/CLIP-convnext_base_w-laion2B-s13B-b82K-augreg
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* https://huggingface.co/laion/CLIP-convnext_base_w_320-laion_aesthetic-s13B-b82K
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## Model Details
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- **Model Type:** Image classification / feature backbone
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- **Model Stats:**
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- Params (M): 200.1
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- GMACs: 44.9
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- Activations (M): 56.3
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- Image size: 256 x 256
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- **Papers:**
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- LAION-5B: An open large-scale dataset for training next generation image-text models: https://arxiv.org/abs/2210.08402
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- A ConvNet for the 2020s: https://arxiv.org/abs/2201.03545
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- Learning Transferable Visual Models From Natural Language Supervision: https://arxiv.org/abs/2103.00020
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- **Original:** https://github.com/mlfoundations/open_clip
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- **Pretrain Dataset:** LAION-2B
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- **Dataset:** ImageNet-1k
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## Model Usage
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### Image Classification
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| 38 |
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```python
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| 39 |
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from urllib.request import urlopen
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from PIL import Image
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import timm
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img = Image.open(
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urlopen('https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'))
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model = timm.create_model('convnext_large_mlp.clip_laion2b_augreg_ft_in1k', pretrained=True)
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| 47 |
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model = model.eval()
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| 48 |
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| 49 |
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# get model specific transforms (normalization, resize)
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| 50 |
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data_config = timm.data.resolve_model_data_config(model)
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| 51 |
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transforms = timm.data.create_transform(**data_config, is_training=False)
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| 52 |
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| 53 |
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output = model(transforms(img).unsqueeze(0)) # unsqueeze single image into batch of 1
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| 54 |
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| 55 |
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top5_probabilities, top5_class_indices = torch.topk(output.softmax(dim=1) * 100, k=5)
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| 56 |
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```
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| 57 |
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| 58 |
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### Feature Map Extraction
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| 59 |
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```python
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| 60 |
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from urllib.request import urlopen
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| 61 |
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from PIL import Image
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| 62 |
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import timm
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| 63 |
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| 64 |
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img = Image.open(
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| 65 |
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urlopen('https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'))
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| 66 |
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| 67 |
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model = timm.create_model(
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| 68 |
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'convnext_large_mlp.clip_laion2b_augreg_ft_in1k',
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| 69 |
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pretrained=True,
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| 70 |
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features_only=True,
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| 71 |
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)
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| 72 |
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model = model.eval()
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| 73 |
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| 74 |
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# get model specific transforms (normalization, resize)
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| 75 |
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data_config = timm.data.resolve_model_data_config(model)
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| 76 |
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transforms = timm.data.create_transform(**data_config, is_training=False)
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| 77 |
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| 78 |
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output = model(transforms(img).unsqueeze(0)) # unsqueeze single image into batch of 1
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| 79 |
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| 80 |
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for o in output:
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| 81 |
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# print shape of each feature map in output
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| 82 |
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# e.g. for convnext_base:
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| 83 |
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# torch.Size([1, 128, 56, 56])
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| 84 |
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# torch.Size([1, 256, 28, 28])
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| 85 |
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# torch.Size([1, 512, 14, 14])
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| 86 |
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# torch.Size([1, 1024, 7, 7])
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| 87 |
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print(o.shape)
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| 88 |
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```
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| 89 |
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### Image Embeddings
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| 91 |
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```python
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| 92 |
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from urllib.request import urlopen
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| 93 |
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from PIL import Image
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| 94 |
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import timm
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| 95 |
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| 96 |
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img = Image.open(
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urlopen('https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'))
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| 98 |
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model = timm.create_model(
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'convnext_large_mlp.clip_laion2b_augreg_ft_in1k',
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pretrained=True,
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| 102 |
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num_classes=0, # remove classifier nn.Linear
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)
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| 104 |
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model = model.eval()
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| 105 |
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| 106 |
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# get model specific transforms (normalization, resize)
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| 107 |
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data_config = timm.data.resolve_model_data_config(model)
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| 108 |
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transforms = timm.data.create_transform(**data_config, is_training=False)
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| 109 |
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| 110 |
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output = model(transforms(img).unsqueeze(0)) # output is (batch_size, num_features) shaped tensor
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| 111 |
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| 112 |
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# or equivalently (without needing to set num_classes=0)
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| 113 |
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| 114 |
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output = model.forward_features(transforms(img).unsqueeze(0))
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| 115 |
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# output is unpooled (ie.e a (batch_size, num_features, H, W) tensor
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| 116 |
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| 117 |
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output = model.forward_head(output, pre_logits=True)
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| 118 |
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# output is (batch_size, num_features) tensor
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| 119 |
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```
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| 120 |
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| 121 |
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## Model Comparison
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| 122 |
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### By Top-1
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| 123 |
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All timing numbers from eager model PyTorch 1.13 on RTX 3090 w/ AMP.
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| 124 |
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| 125 |
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|model |top1 |top5 |img_size|param_count|gmacs |macts |samples_per_sec|batch_size|
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| 126 |
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|----------------------------------------------|------|------|--------|-----------|------|------|---------------|----------|
|
| 127 |
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|[convnextv2_huge.fcmae_ft_in22k_in1k_512](https://huggingface.co/timm/convnextv2_huge.fcmae_ft_in22k_in1k_512)|88.848|98.742|512 |660.29 |600.81|413.07|28.58 |48 |
|
| 128 |
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|[convnextv2_huge.fcmae_ft_in22k_in1k_384](https://huggingface.co/timm/convnextv2_huge.fcmae_ft_in22k_in1k_384)|88.668|98.738|384 |660.29 |337.96|232.35|50.56 |64 |
|
| 129 |
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|[convnextv2_large.fcmae_ft_in22k_in1k_384](https://huggingface.co/timm/convnextv2_large.fcmae_ft_in22k_in1k_384)|88.196|98.532|384 |197.96 |101.1 |126.74|128.94 |128 |
|
| 130 |
+
|[convnext_xlarge.fb_in22k_ft_in1k_384](https://huggingface.co/timm/convnext_xlarge.fb_in22k_ft_in1k_384)|87.75 |98.556|384 |350.2 |179.2 |168.99|124.85 |192 |
|
| 131 |
+
|[convnextv2_base.fcmae_ft_in22k_in1k_384](https://huggingface.co/timm/convnextv2_base.fcmae_ft_in22k_in1k_384)|87.646|98.422|384 |88.72 |45.21 |84.49 |209.51 |256 |
|
| 132 |
+
|[convnext_large.fb_in22k_ft_in1k_384](https://huggingface.co/timm/convnext_large.fb_in22k_ft_in1k_384)|87.476|98.382|384 |197.77 |101.1 |126.74|194.66 |256 |
|
| 133 |
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|[convnext_large_mlp.clip_laion2b_augreg_ft_in1k](https://huggingface.co/timm/convnext_large_mlp.clip_laion2b_augreg_ft_in1k)|87.344|98.218|256 |200.13 |44.94 |56.33 |438.08 |256 |
|
| 134 |
+
|[convnextv2_large.fcmae_ft_in22k_in1k](https://huggingface.co/timm/convnextv2_large.fcmae_ft_in22k_in1k)|87.26 |98.248|224 |197.96 |34.4 |43.13 |376.84 |256 |
|
| 135 |
+
|[convnext_xlarge.fb_in22k_ft_in1k](https://huggingface.co/timm/convnext_xlarge.fb_in22k_ft_in1k)|87.002|98.208|224 |350.2 |60.98 |57.5 |368.01 |256 |
|
| 136 |
+
|[convnext_base.fb_in22k_ft_in1k_384](https://huggingface.co/timm/convnext_base.fb_in22k_ft_in1k_384)|86.796|98.264|384 |88.59 |45.21 |84.49 |366.54 |256 |
|
| 137 |
+
|[convnextv2_base.fcmae_ft_in22k_in1k](https://huggingface.co/timm/convnextv2_base.fcmae_ft_in22k_in1k)|86.74 |98.022|224 |88.72 |15.38 |28.75 |624.23 |256 |
|
| 138 |
+
|[convnext_large.fb_in22k_ft_in1k](https://huggingface.co/timm/convnext_large.fb_in22k_ft_in1k)|86.636|98.028|224 |197.77 |34.4 |43.13 |581.43 |256 |
|
| 139 |
+
|[convnext_base.clip_laiona_augreg_ft_in1k_384](https://huggingface.co/timm/convnext_base.clip_laiona_augreg_ft_in1k_384)|86.504|97.97 |384 |88.59 |45.21 |84.49 |368.14 |256 |
|
| 140 |
+
|[convnextv2_huge.fcmae_ft_in1k](https://huggingface.co/timm/convnextv2_huge.fcmae_ft_in1k)|86.256|97.75 |224 |660.29 |115.0 |79.07 |154.72 |256 |
|
| 141 |
+
|[convnext_small.in12k_ft_in1k_384](https://huggingface.co/timm/convnext_small.in12k_ft_in1k_384)|86.182|97.92 |384 |50.22 |25.58 |63.37 |516.19 |256 |
|
| 142 |
+
|[convnext_base.clip_laion2b_augreg_ft_in1k](https://huggingface.co/timm/convnext_base.clip_laion2b_augreg_ft_in1k)|86.154|97.68 |256 |88.59 |20.09 |37.55 |819.86 |256 |
|
| 143 |
+
|[convnext_base.fb_in22k_ft_in1k](https://huggingface.co/timm/convnext_base.fb_in22k_ft_in1k)|85.822|97.866|224 |88.59 |15.38 |28.75 |1037.66 |256 |
|
| 144 |
+
|[convnext_small.fb_in22k_ft_in1k_384](https://huggingface.co/timm/convnext_small.fb_in22k_ft_in1k_384)|85.778|97.886|384 |50.22 |25.58 |63.37 |518.95 |256 |
|
| 145 |
+
|[convnextv2_large.fcmae_ft_in1k](https://huggingface.co/timm/convnextv2_large.fcmae_ft_in1k)|85.742|97.584|224 |197.96 |34.4 |43.13 |375.23 |256 |
|
| 146 |
+
|[convnext_small.in12k_ft_in1k](https://huggingface.co/timm/convnext_small.in12k_ft_in1k)|85.174|97.506|224 |50.22 |8.71 |21.56 |1474.31 |256 |
|
| 147 |
+
|[convnext_tiny.in12k_ft_in1k_384](https://huggingface.co/timm/convnext_tiny.in12k_ft_in1k_384)|85.118|97.608|384 |28.59 |13.14 |39.48 |856.76 |256 |
|
| 148 |
+
|[convnextv2_tiny.fcmae_ft_in22k_in1k_384](https://huggingface.co/timm/convnextv2_tiny.fcmae_ft_in22k_in1k_384)|85.112|97.63 |384 |28.64 |13.14 |39.48 |491.32 |256 |
|
| 149 |
+
|[convnextv2_base.fcmae_ft_in1k](https://huggingface.co/timm/convnextv2_base.fcmae_ft_in1k)|84.874|97.09 |224 |88.72 |15.38 |28.75 |625.33 |256 |
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| 150 |
+
|[convnext_small.fb_in22k_ft_in1k](https://huggingface.co/timm/convnext_small.fb_in22k_ft_in1k)|84.562|97.394|224 |50.22 |8.71 |21.56 |1478.29 |256 |
|
| 151 |
+
|[convnext_large.fb_in1k](https://huggingface.co/timm/convnext_large.fb_in1k)|84.282|96.892|224 |197.77 |34.4 |43.13 |584.28 |256 |
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| 152 |
+
|[convnext_tiny.in12k_ft_in1k](https://huggingface.co/timm/convnext_tiny.in12k_ft_in1k)|84.186|97.124|224 |28.59 |4.47 |13.44 |2433.7 |256 |
|
| 153 |
+
|[convnext_tiny.fb_in22k_ft_in1k_384](https://huggingface.co/timm/convnext_tiny.fb_in22k_ft_in1k_384)|84.084|97.14 |384 |28.59 |13.14 |39.48 |862.95 |256 |
|
| 154 |
+
|[convnextv2_tiny.fcmae_ft_in22k_in1k](https://huggingface.co/timm/convnextv2_tiny.fcmae_ft_in22k_in1k)|83.894|96.964|224 |28.64 |4.47 |13.44 |1452.72 |256 |
|
| 155 |
+
|[convnext_base.fb_in1k](https://huggingface.co/timm/convnext_base.fb_in1k)|83.82 |96.746|224 |88.59 |15.38 |28.75 |1054.0 |256 |
|
| 156 |
+
|[convnextv2_nano.fcmae_ft_in22k_in1k_384](https://huggingface.co/timm/convnextv2_nano.fcmae_ft_in22k_in1k_384)|83.37 |96.742|384 |15.62 |7.22 |24.61 |801.72 |256 |
|
| 157 |
+
|[convnext_small.fb_in1k](https://huggingface.co/timm/convnext_small.fb_in1k)|83.142|96.434|224 |50.22 |8.71 |21.56 |1464.0 |256 |
|
| 158 |
+
|[convnextv2_tiny.fcmae_ft_in1k](https://huggingface.co/timm/convnextv2_tiny.fcmae_ft_in1k)|82.92 |96.284|224 |28.64 |4.47 |13.44 |1425.62 |256 |
|
| 159 |
+
|[convnext_tiny.fb_in22k_ft_in1k](https://huggingface.co/timm/convnext_tiny.fb_in22k_ft_in1k)|82.898|96.616|224 |28.59 |4.47 |13.44 |2480.88 |256 |
|
| 160 |
+
|[convnext_nano.in12k_ft_in1k](https://huggingface.co/timm/convnext_nano.in12k_ft_in1k)|82.282|96.344|224 |15.59 |2.46 |8.37 |3926.52 |256 |
|
| 161 |
+
|[convnext_tiny_hnf.a2h_in1k](https://huggingface.co/timm/convnext_tiny_hnf.a2h_in1k)|82.216|95.852|224 |28.59 |4.47 |13.44 |2529.75 |256 |
|
| 162 |
+
|[convnext_tiny.fb_in1k](https://huggingface.co/timm/convnext_tiny.fb_in1k)|82.066|95.854|224 |28.59 |4.47 |13.44 |2346.26 |256 |
|
| 163 |
+
|[convnextv2_nano.fcmae_ft_in22k_in1k](https://huggingface.co/timm/convnextv2_nano.fcmae_ft_in22k_in1k)|82.03 |96.166|224 |15.62 |2.46 |8.37 |2300.18 |256 |
|
| 164 |
+
|[convnextv2_nano.fcmae_ft_in1k](https://huggingface.co/timm/convnextv2_nano.fcmae_ft_in1k)|81.83 |95.738|224 |15.62 |2.46 |8.37 |2321.48 |256 |
|
| 165 |
+
|[convnext_nano_ols.d1h_in1k](https://huggingface.co/timm/convnext_nano_ols.d1h_in1k)|80.866|95.246|224 |15.65 |2.65 |9.38 |3523.85 |256 |
|
| 166 |
+
|[convnext_nano.d1h_in1k](https://huggingface.co/timm/convnext_nano.d1h_in1k)|80.768|95.334|224 |15.59 |2.46 |8.37 |3915.58 |256 |
|
| 167 |
+
|[convnextv2_pico.fcmae_ft_in1k](https://huggingface.co/timm/convnextv2_pico.fcmae_ft_in1k)|80.304|95.072|224 |9.07 |1.37 |6.1 |3274.57 |256 |
|
| 168 |
+
|[convnext_pico.d1_in1k](https://huggingface.co/timm/convnext_pico.d1_in1k)|79.526|94.558|224 |9.05 |1.37 |6.1 |5686.88 |256 |
|
| 169 |
+
|[convnext_pico_ols.d1_in1k](https://huggingface.co/timm/convnext_pico_ols.d1_in1k)|79.522|94.692|224 |9.06 |1.43 |6.5 |5422.46 |256 |
|
| 170 |
+
|[convnextv2_femto.fcmae_ft_in1k](https://huggingface.co/timm/convnextv2_femto.fcmae_ft_in1k)|78.488|93.98 |224 |5.23 |0.79 |4.57 |4264.2 |256 |
|
| 171 |
+
|[convnext_femto_ols.d1_in1k](https://huggingface.co/timm/convnext_femto_ols.d1_in1k)|77.86 |93.83 |224 |5.23 |0.82 |4.87 |6910.6 |256 |
|
| 172 |
+
|[convnext_femto.d1_in1k](https://huggingface.co/timm/convnext_femto.d1_in1k)|77.454|93.68 |224 |5.22 |0.79 |4.57 |7189.92 |256 |
|
| 173 |
+
|[convnextv2_atto.fcmae_ft_in1k](https://huggingface.co/timm/convnextv2_atto.fcmae_ft_in1k)|76.664|93.044|224 |3.71 |0.55 |3.81 |4728.91 |256 |
|
| 174 |
+
|[convnext_atto_ols.a2_in1k](https://huggingface.co/timm/convnext_atto_ols.a2_in1k)|75.88 |92.846|224 |3.7 |0.58 |4.11 |7963.16 |256 |
|
| 175 |
+
|[convnext_atto.d2_in1k](https://huggingface.co/timm/convnext_atto.d2_in1k)|75.664|92.9 |224 |3.7 |0.55 |3.81 |8439.22 |256 |
|
| 176 |
+
|
| 177 |
+
### By Throughput (samples / sec)
|
| 178 |
+
All timing numbers from eager model PyTorch 1.13 on RTX 3090 w/ AMP.
|
| 179 |
+
|
| 180 |
+
|model |top1 |top5 |img_size|param_count|gmacs |macts |samples_per_sec|batch_size|
|
| 181 |
+
|----------------------------------------------|------|------|--------|-----------|------|------|---------------|----------|
|
| 182 |
+
|[convnext_atto.d2_in1k](https://huggingface.co/timm/convnext_atto.d2_in1k)|75.664|92.9 |224 |3.7 |0.55 |3.81 |8439.22 |256 |
|
| 183 |
+
|[convnext_atto_ols.a2_in1k](https://huggingface.co/timm/convnext_atto_ols.a2_in1k)|75.88 |92.846|224 |3.7 |0.58 |4.11 |7963.16 |256 |
|
| 184 |
+
|[convnext_femto.d1_in1k](https://huggingface.co/timm/convnext_femto.d1_in1k)|77.454|93.68 |224 |5.22 |0.79 |4.57 |7189.92 |256 |
|
| 185 |
+
|[convnext_femto_ols.d1_in1k](https://huggingface.co/timm/convnext_femto_ols.d1_in1k)|77.86 |93.83 |224 |5.23 |0.82 |4.87 |6910.6 |256 |
|
| 186 |
+
|[convnext_pico.d1_in1k](https://huggingface.co/timm/convnext_pico.d1_in1k)|79.526|94.558|224 |9.05 |1.37 |6.1 |5686.88 |256 |
|
| 187 |
+
|[convnext_pico_ols.d1_in1k](https://huggingface.co/timm/convnext_pico_ols.d1_in1k)|79.522|94.692|224 |9.06 |1.43 |6.5 |5422.46 |256 |
|
| 188 |
+
|[convnextv2_atto.fcmae_ft_in1k](https://huggingface.co/timm/convnextv2_atto.fcmae_ft_in1k)|76.664|93.044|224 |3.71 |0.55 |3.81 |4728.91 |256 |
|
| 189 |
+
|[convnextv2_femto.fcmae_ft_in1k](https://huggingface.co/timm/convnextv2_femto.fcmae_ft_in1k)|78.488|93.98 |224 |5.23 |0.79 |4.57 |4264.2 |256 |
|
| 190 |
+
|[convnext_nano.in12k_ft_in1k](https://huggingface.co/timm/convnext_nano.in12k_ft_in1k)|82.282|96.344|224 |15.59 |2.46 |8.37 |3926.52 |256 |
|
| 191 |
+
|[convnext_nano.d1h_in1k](https://huggingface.co/timm/convnext_nano.d1h_in1k)|80.768|95.334|224 |15.59 |2.46 |8.37 |3915.58 |256 |
|
| 192 |
+
|[convnext_nano_ols.d1h_in1k](https://huggingface.co/timm/convnext_nano_ols.d1h_in1k)|80.866|95.246|224 |15.65 |2.65 |9.38 |3523.85 |256 |
|
| 193 |
+
|[convnextv2_pico.fcmae_ft_in1k](https://huggingface.co/timm/convnextv2_pico.fcmae_ft_in1k)|80.304|95.072|224 |9.07 |1.37 |6.1 |3274.57 |256 |
|
| 194 |
+
|[convnext_tiny_hnf.a2h_in1k](https://huggingface.co/timm/convnext_tiny_hnf.a2h_in1k)|82.216|95.852|224 |28.59 |4.47 |13.44 |2529.75 |256 |
|
| 195 |
+
|[convnext_tiny.fb_in22k_ft_in1k](https://huggingface.co/timm/convnext_tiny.fb_in22k_ft_in1k)|82.898|96.616|224 |28.59 |4.47 |13.44 |2480.88 |256 |
|
| 196 |
+
|[convnext_tiny.in12k_ft_in1k](https://huggingface.co/timm/convnext_tiny.in12k_ft_in1k)|84.186|97.124|224 |28.59 |4.47 |13.44 |2433.7 |256 |
|
| 197 |
+
|[convnext_tiny.fb_in1k](https://huggingface.co/timm/convnext_tiny.fb_in1k)|82.066|95.854|224 |28.59 |4.47 |13.44 |2346.26 |256 |
|
| 198 |
+
|[convnextv2_nano.fcmae_ft_in1k](https://huggingface.co/timm/convnextv2_nano.fcmae_ft_in1k)|81.83 |95.738|224 |15.62 |2.46 |8.37 |2321.48 |256 |
|
| 199 |
+
|[convnextv2_nano.fcmae_ft_in22k_in1k](https://huggingface.co/timm/convnextv2_nano.fcmae_ft_in22k_in1k)|82.03 |96.166|224 |15.62 |2.46 |8.37 |2300.18 |256 |
|
| 200 |
+
|[convnext_small.fb_in22k_ft_in1k](https://huggingface.co/timm/convnext_small.fb_in22k_ft_in1k)|84.562|97.394|224 |50.22 |8.71 |21.56 |1478.29 |256 |
|
| 201 |
+
|[convnext_small.in12k_ft_in1k](https://huggingface.co/timm/convnext_small.in12k_ft_in1k)|85.174|97.506|224 |50.22 |8.71 |21.56 |1474.31 |256 |
|
| 202 |
+
|[convnext_small.fb_in1k](https://huggingface.co/timm/convnext_small.fb_in1k)|83.142|96.434|224 |50.22 |8.71 |21.56 |1464.0 |256 |
|
| 203 |
+
|[convnextv2_tiny.fcmae_ft_in22k_in1k](https://huggingface.co/timm/convnextv2_tiny.fcmae_ft_in22k_in1k)|83.894|96.964|224 |28.64 |4.47 |13.44 |1452.72 |256 |
|
| 204 |
+
|[convnextv2_tiny.fcmae_ft_in1k](https://huggingface.co/timm/convnextv2_tiny.fcmae_ft_in1k)|82.92 |96.284|224 |28.64 |4.47 |13.44 |1425.62 |256 |
|
| 205 |
+
|[convnext_base.fb_in1k](https://huggingface.co/timm/convnext_base.fb_in1k)|83.82 |96.746|224 |88.59 |15.38 |28.75 |1054.0 |256 |
|
| 206 |
+
|[convnext_base.fb_in22k_ft_in1k](https://huggingface.co/timm/convnext_base.fb_in22k_ft_in1k)|85.822|97.866|224 |88.59 |15.38 |28.75 |1037.66 |256 |
|
| 207 |
+
|[convnext_tiny.fb_in22k_ft_in1k_384](https://huggingface.co/timm/convnext_tiny.fb_in22k_ft_in1k_384)|84.084|97.14 |384 |28.59 |13.14 |39.48 |862.95 |256 |
|
| 208 |
+
|[convnext_tiny.in12k_ft_in1k_384](https://huggingface.co/timm/convnext_tiny.in12k_ft_in1k_384)|85.118|97.608|384 |28.59 |13.14 |39.48 |856.76 |256 |
|
| 209 |
+
|[convnext_base.clip_laion2b_augreg_ft_in1k](https://huggingface.co/timm/convnext_base.clip_laion2b_augreg_ft_in1k)|86.154|97.68 |256 |88.59 |20.09 |37.55 |819.86 |256 |
|
| 210 |
+
|[convnextv2_nano.fcmae_ft_in22k_in1k_384](https://huggingface.co/timm/convnextv2_nano.fcmae_ft_in22k_in1k_384)|83.37 |96.742|384 |15.62 |7.22 |24.61 |801.72 |256 |
|
| 211 |
+
|[convnextv2_base.fcmae_ft_in1k](https://huggingface.co/timm/convnextv2_base.fcmae_ft_in1k)|84.874|97.09 |224 |88.72 |15.38 |28.75 |625.33 |256 |
|
| 212 |
+
|[convnextv2_base.fcmae_ft_in22k_in1k](https://huggingface.co/timm/convnextv2_base.fcmae_ft_in22k_in1k)|86.74 |98.022|224 |88.72 |15.38 |28.75 |624.23 |256 |
|
| 213 |
+
|[convnext_large.fb_in1k](https://huggingface.co/timm/convnext_large.fb_in1k)|84.282|96.892|224 |197.77 |34.4 |43.13 |584.28 |256 |
|
| 214 |
+
|[convnext_large.fb_in22k_ft_in1k](https://huggingface.co/timm/convnext_large.fb_in22k_ft_in1k)|86.636|98.028|224 |197.77 |34.4 |43.13 |581.43 |256 |
|
| 215 |
+
|[convnext_small.fb_in22k_ft_in1k_384](https://huggingface.co/timm/convnext_small.fb_in22k_ft_in1k_384)|85.778|97.886|384 |50.22 |25.58 |63.37 |518.95 |256 |
|
| 216 |
+
|[convnext_small.in12k_ft_in1k_384](https://huggingface.co/timm/convnext_small.in12k_ft_in1k_384)|86.182|97.92 |384 |50.22 |25.58 |63.37 |516.19 |256 |
|
| 217 |
+
|[convnextv2_tiny.fcmae_ft_in22k_in1k_384](https://huggingface.co/timm/convnextv2_tiny.fcmae_ft_in22k_in1k_384)|85.112|97.63 |384 |28.64 |13.14 |39.48 |491.32 |256 |
|
| 218 |
+
|[convnext_large_mlp.clip_laion2b_augreg_ft_in1k](https://huggingface.co/timm/convnext_large_mlp.clip_laion2b_augreg_ft_in1k)|87.344|98.218|256 |200.13 |44.94 |56.33 |438.08 |256 |
|
| 219 |
+
|[convnextv2_large.fcmae_ft_in22k_in1k](https://huggingface.co/timm/convnextv2_large.fcmae_ft_in22k_in1k)|87.26 |98.248|224 |197.96 |34.4 |43.13 |376.84 |256 |
|
| 220 |
+
|[convnextv2_large.fcmae_ft_in1k](https://huggingface.co/timm/convnextv2_large.fcmae_ft_in1k)|85.742|97.584|224 |197.96 |34.4 |43.13 |375.23 |256 |
|
| 221 |
+
|[convnext_base.clip_laiona_augreg_ft_in1k_384](https://huggingface.co/timm/convnext_base.clip_laiona_augreg_ft_in1k_384)|86.504|97.97 |384 |88.59 |45.21 |84.49 |368.14 |256 |
|
| 222 |
+
|[convnext_xlarge.fb_in22k_ft_in1k](https://huggingface.co/timm/convnext_xlarge.fb_in22k_ft_in1k)|87.002|98.208|224 |350.2 |60.98 |57.5 |368.01 |256 |
|
| 223 |
+
|[convnext_base.fb_in22k_ft_in1k_384](https://huggingface.co/timm/convnext_base.fb_in22k_ft_in1k_384)|86.796|98.264|384 |88.59 |45.21 |84.49 |366.54 |256 |
|
| 224 |
+
|[convnextv2_base.fcmae_ft_in22k_in1k_384](https://huggingface.co/timm/convnextv2_base.fcmae_ft_in22k_in1k_384)|87.646|98.422|384 |88.72 |45.21 |84.49 |209.51 |256 |
|
| 225 |
+
|[convnext_large.fb_in22k_ft_in1k_384](https://huggingface.co/timm/convnext_large.fb_in22k_ft_in1k_384)|87.476|98.382|384 |197.77 |101.1 |126.74|194.66 |256 |
|
| 226 |
+
|[convnextv2_huge.fcmae_ft_in1k](https://huggingface.co/timm/convnextv2_huge.fcmae_ft_in1k)|86.256|97.75 |224 |660.29 |115.0 |79.07 |154.72 |256 |
|
| 227 |
+
|[convnextv2_large.fcmae_ft_in22k_in1k_384](https://huggingface.co/timm/convnextv2_large.fcmae_ft_in22k_in1k_384)|88.196|98.532|384 |197.96 |101.1 |126.74|128.94 |128 |
|
| 228 |
+
|[convnext_xlarge.fb_in22k_ft_in1k_384](https://huggingface.co/timm/convnext_xlarge.fb_in22k_ft_in1k_384)|87.75 |98.556|384 |350.2 |179.2 |168.99|124.85 |192 |
|
| 229 |
+
|[convnextv2_huge.fcmae_ft_in22k_in1k_384](https://huggingface.co/timm/convnextv2_huge.fcmae_ft_in22k_in1k_384)|88.668|98.738|384 |660.29 |337.96|232.35|50.56 |64 |
|
| 230 |
+
|[convnextv2_huge.fcmae_ft_in22k_in1k_512](https://huggingface.co/timm/convnextv2_huge.fcmae_ft_in22k_in1k_512)|88.848|98.742|512 |660.29 |600.81|413.07|28.58 |48 |
|
| 231 |
+
|
| 232 |
+
## Citation
|
| 233 |
+
```bibtex
|
| 234 |
+
@software{ilharco_gabriel_2021_5143773,
|
| 235 |
+
author = {Ilharco, Gabriel and
|
| 236 |
+
Wortsman, Mitchell and
|
| 237 |
+
Wightman, Ross and
|
| 238 |
+
Gordon, Cade and
|
| 239 |
+
Carlini, Nicholas and
|
| 240 |
+
Taori, Rohan and
|
| 241 |
+
Dave, Achal and
|
| 242 |
+
Shankar, Vaishaal and
|
| 243 |
+
Namkoong, Hongseok and
|
| 244 |
+
Miller, John and
|
| 245 |
+
Hajishirzi, Hannaneh and
|
| 246 |
+
Farhadi, Ali and
|
| 247 |
+
Schmidt, Ludwig},
|
| 248 |
+
title = {OpenCLIP},
|
| 249 |
+
month = jul,
|
| 250 |
+
year = 2021,
|
| 251 |
+
note = {If you use this software, please cite it as below.},
|
| 252 |
+
publisher = {Zenodo},
|
| 253 |
+
version = {0.1},
|
| 254 |
+
doi = {10.5281/zenodo.5143773},
|
| 255 |
+
url = {https://doi.org/10.5281/zenodo.5143773}
|
| 256 |
+
}
|
| 257 |
+
```
|
| 258 |
+
```bibtex
|
| 259 |
+
@inproceedings{schuhmann2022laionb,
|
| 260 |
+
title={{LAION}-5B: An open large-scale dataset for training next generation image-text models},
|
| 261 |
+
author={Christoph Schuhmann and
|
| 262 |
+
Romain Beaumont and
|
| 263 |
+
Richard Vencu and
|
| 264 |
+
Cade W Gordon and
|
| 265 |
+
Ross Wightman and
|
| 266 |
+
Mehdi Cherti and
|
| 267 |
+
Theo Coombes and
|
| 268 |
+
Aarush Katta and
|
| 269 |
+
Clayton Mullis and
|
| 270 |
+
Mitchell Wortsman and
|
| 271 |
+
Patrick Schramowski and
|
| 272 |
+
Srivatsa R Kundurthy and
|
| 273 |
+
Katherine Crowson and
|
| 274 |
+
Ludwig Schmidt and
|
| 275 |
+
Robert Kaczmarczyk and
|
| 276 |
+
Jenia Jitsev},
|
| 277 |
+
booktitle={Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
|
| 278 |
+
year={2022},
|
| 279 |
+
url={https://openreview.net/forum?id=M3Y74vmsMcY}
|
| 280 |
+
}
|
| 281 |
+
```
|
| 282 |
+
```bibtex
|
| 283 |
+
@misc{rw2019timm,
|
| 284 |
+
author = {Ross Wightman},
|
| 285 |
+
title = {PyTorch Image Models},
|
| 286 |
+
year = {2019},
|
| 287 |
+
publisher = {GitHub},
|
| 288 |
+
journal = {GitHub repository},
|
| 289 |
+
doi = {10.5281/zenodo.4414861},
|
| 290 |
+
howpublished = {\url{https://github.com/rwightman/pytorch-image-models}}
|
| 291 |
+
}
|
| 292 |
+
```
|
| 293 |
+
```bibtex
|
| 294 |
+
@inproceedings{Radford2021LearningTV,
|
| 295 |
+
title={Learning Transferable Visual Models From Natural Language Supervision},
|
| 296 |
+
author={Alec Radford and Jong Wook Kim and Chris Hallacy and A. Ramesh and Gabriel Goh and Sandhini Agarwal and Girish Sastry and Amanda Askell and Pamela Mishkin and Jack Clark and Gretchen Krueger and Ilya Sutskever},
|
| 297 |
+
booktitle={ICML},
|
| 298 |
+
year={2021}
|
| 299 |
+
}
|
| 300 |
+
```
|
| 301 |
+
```bibtex
|
| 302 |
+
@article{liu2022convnet,
|
| 303 |
+
author = {Zhuang Liu and Hanzi Mao and Chao-Yuan Wu and Christoph Feichtenhofer and Trevor Darrell and Saining Xie},
|
| 304 |
+
title = {A ConvNet for the 2020s},
|
| 305 |
+
journal = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
|
| 306 |
+
year = {2022},
|
| 307 |
+
}
|
| 308 |
+
```
|
config.json
ADDED
|
@@ -0,0 +1,35 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architecture": "convnext_large_mlp",
|
| 3 |
+
"num_classes": 1000,
|
| 4 |
+
"num_features": 1536,
|
| 5 |
+
"pretrained_cfg": {
|
| 6 |
+
"tag": "clip_laion2b_augreg_ft_in1k",
|
| 7 |
+
"custom_load": false,
|
| 8 |
+
"input_size": [
|
| 9 |
+
3,
|
| 10 |
+
256,
|
| 11 |
+
256
|
| 12 |
+
],
|
| 13 |
+
"fixed_input_size": false,
|
| 14 |
+
"interpolation": "bicubic",
|
| 15 |
+
"crop_pct": 1.0,
|
| 16 |
+
"crop_mode": "center",
|
| 17 |
+
"mean": [
|
| 18 |
+
0.48145466,
|
| 19 |
+
0.4578275,
|
| 20 |
+
0.40821073
|
| 21 |
+
],
|
| 22 |
+
"std": [
|
| 23 |
+
0.26862954,
|
| 24 |
+
0.26130258,
|
| 25 |
+
0.27577711
|
| 26 |
+
],
|
| 27 |
+
"num_classes": 1000,
|
| 28 |
+
"pool_size": [
|
| 29 |
+
8,
|
| 30 |
+
8
|
| 31 |
+
],
|
| 32 |
+
"first_conv": "stem.0",
|
| 33 |
+
"classifier": "head.fc"
|
| 34 |
+
}
|
| 35 |
+
}
|
pytorch_model.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6f8be99b2929e79e0e59483104a7e1bc1eb7d2a56badcd78e655cdb46310edbe
|
| 3 |
+
size 800639221
|