File size: 23,629 Bytes
add7c44
 
 
5446ac0
338bdbd
88eecb2
346303e
ebc1fba
ec21514
4eb737b
6481d9a
ab584f1
3c1d630
3cafca6
6199aef
b032959
aea36d6
4cdf12c
924c64c
8c79b50
df2c466
07626c5
956aa07
e1bf17d
add7c44
3ecf9a0
3903ba7
1126c99
88492b3
7578b66
7ff7f08
5222cef
76117de
2bfa87e
c4d7899
908416c
b206523
c917c7e
8c33938
0f016db
66241b7
04692f1
c54f572
d2c499c
f657291
4ce3af9
add7c44
 
 
 
 
 
 
 
 
 
 
 
 
07626c5
76117de
3cafca6
76117de
 
 
 
 
 
 
 
3cafca6
76117de
 
 
 
 
 
 
3cafca6
76117de
ec21514
76117de
ebc1fba
 
 
ec21514
ebc1fba
76117de
3cafca6
76117de
956aa07
76117de
956aa07
 
 
 
 
76117de
3cafca6
76117de
3cafca6
76117de
 
 
3cafca6
76117de
 
6199aef
 
 
 
 
 
 
 
3cafca6
76117de
 
 
 
 
 
 
3cafca6
8c79b50
924c64c
8c79b50
924c64c
 
 
 
8c79b50
df2c466
 
 
 
 
 
 
 
07626c5
 
 
 
 
 
 
 
3cafca6
76117de
5446ac0
76117de
5446ac0
 
 
 
 
76117de
b032959
 
4cdf12c
b032959
4cdf12c
 
 
 
b032959
3ecf9a0
 
 
 
 
 
 
 
3cafca6
76117de
 
 
 
 
 
 
3cafca6
76117de
7578b66
76117de
7578b66
 
 
 
 
76117de
7ff7f08
 
5222cef
7ff7f08
 
 
5222cef
7ff7f08
 
3cafca6
76117de
2bfa87e
76117de
6481d9a
 
908416c
6481d9a
c4d7899
6481d9a
2bfa87e
76117de
c917c7e
 
 
 
 
 
 
 
8c33938
 
 
 
 
 
 
 
3cafca6
0f016db
 
 
 
 
 
 
3cafca6
76117de
c54f572
add7c44
c54f572
 
 
 
 
 
76117de
3cafca6
76117de
f657291
76117de
f657291
 
 
 
add7c44
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
---
pipeline_tag: image-classification
base_model:
- timm/caformer_s18.sail_in22k
- timm/convformer_m36.sail_in22k_ft_in1k
- timm/convformer_s36.sail_in1k_384
- timm/convmixer_1024_20_ks9_p14.in1k
- timm/convnext_nano.r384_in12k_ft_in1k
- timm/convnext_pico.d1_in1k
- timm/convnextv2_atto.fcmae_ft_in1k
- timm/ecaresnet50t.a1_in1k
- timm/efficientnet_b5.sw_in12k
- timm/efficientvit_b1.r256_in1k
- timm/efficientvit_b2.r256_in1k
- timm/efficientvit_l1.r224_in1k
- timm/fbnetv3_b.ra2_in1k
- timm/ghostnetv2_100.in1k
- timm/hardcorenas_f.miil_green_in1k
- timm/hgnetv2_b3.ssld_stage1_in22k_in1k
- timm/hgnetv2_b4.ssld_stage2_ft_in1k
- timm/inception_resnet_v2.tf_in1k
- timm/inception_v4.tf_in1k
- timm/mobilenet_edgetpu_v2_m.ra4_e3600_r224_in1k
- timm/mobilenetv2_100.ra_in1k
- timm/mobilevitv2_050.cvnets_in1k
- timm/nest_base_jx.goog_in1k
- timm/nextvit_base.bd_in1k
- timm/regnetx_040.pycls_in1k
- timm/regnetx_080.tv2_in1k
- timm/regnety_160.lion_in12k_ft_in1k
- timm/repghostnet_050.in1k
- timm/repghostnet_200.in1k
- timm/repvgg_b1.rvgg_in1k
- timm/resnet34.a3_in1k
- timm/resnet50d.a1_in1k
- timm/resnet101d.ra2_in1k
- timm/resnetaa50.a1h_in1k
- timm/resnetv2_101x1_bit.goog_in21k_ft_in1k
- timm/rexnetr_300.sw_in12k_ft_in1k
- timm/swin_base_patch4_window7_224.ms_in1k
- timm/vit_base_patch16_clip_384.laion2b_ft_in12k_in1k
- timm/vit_base_r50_s16_384.orig_in21k_ft_in1k
- timm/vit_betwixt_patch16_reg1_gap_256.sbb_in1k
- timm/vit_little_patch16_reg4_gap_256.sbb_in1k
- timm/xcit_medium_24_p16_384.fb_dist_in1k
- timm/xcit_small_24_p16_224.fb_in1k
language:
- en
tags:
- timm
- image
- dghs-realutils
library_name: dghs-imgutils
---

ONNX export version from [TIMM](https://huggingface.co/timm).

# Models

43 models exported from TIMM in total.

## ByobNet

2 models with model class `ByobNet`.

| Name                                                                                   | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model   | Architecture    | Created At   |
|:---------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:--------|:----------------|:-------------|
| [repvgg_b1.rvgg_in1k](https://huggingface.co/timm/repvgg_b1.rvgg_in1k)                 | 57.3M    | 13.1G   |          224 | True           |       2048 |      1000 | imagenet-1k | ByobNet | repvgg_b1       | 2023-03-22   |
| [mobilevitv2_050.cvnets_in1k](https://huggingface.co/timm/mobilevitv2_050.cvnets_in1k) | 1.4M     | 464.6M  |          256 | True           |        256 |      1000 | imagenet-1k | ByobNet | mobilevitv2_050 | 2023-04-24   |

## ConvMixer

1 model with model class `ConvMixer`.

| Name                                                                                         | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model     | Architecture              | Created At   |
|:---------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:----------|:--------------------------|:-------------|
| [convmixer_1024_20_ks9_p14.in1k](https://huggingface.co/timm/convmixer_1024_20_ks9_p14.in1k) | 24.4M    | 6.0G    |          224 | True           |       1024 |      1000 | imagenet-1k | ConvMixer | convmixer_1024_20_ks9_p14 | 2023-04-24   |

## ConvNeXt

3 models with model class `ConvNeXt`.

| Name                                                                                             | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model    | Architecture    | Created At   |
|:-------------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:---------|:----------------|:-------------|
| [convnext_nano.r384_in12k_ft_in1k](https://huggingface.co/timm/convnext_nano.r384_in12k_ft_in1k) | 15.6M    | 7.2G    |          384 | True           |        640 |      1000 | imagenet-1k | ConvNeXt | convnext_nano   | 2024-12-31   |
| [convnext_pico.d1_in1k](https://huggingface.co/timm/convnext_pico.d1_in1k)                       | 9.0M     | 1.4G    |          224 | True           |        512 |      1000 | imagenet-1k | ConvNeXt | convnext_pico   | 2022-12-13   |
| [convnextv2_atto.fcmae_ft_in1k](https://huggingface.co/timm/convnextv2_atto.fcmae_ft_in1k)       | 3.7M     | 547.3M  |          224 | True           |        320 |      1000 | imagenet-1k | ConvNeXt | convnextv2_atto | 2023-01-05   |

## EfficientNet

3 models with model class `EfficientNet`.

| Name                                                                                                                 | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset      | Model        | Architecture           | Created At   |
|:---------------------------------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:-------------|:-------------|:-----------------------|:-------------|
| [efficientnet_b5.sw_in12k](https://huggingface.co/timm/efficientnet_b5.sw_in12k)                                     | 52.4M    | 8.1G    |          416 | True           |       2048 |     11821 | imagenet-12k | EfficientNet | efficientnet_b5        | 2022-12-12   |
| [mobilenet_edgetpu_v2_m.ra4_e3600_r224_in1k](https://huggingface.co/timm/mobilenet_edgetpu_v2_m.ra4_e3600_r224_in1k) | 8.4M     | 1.8G    |          224 | True           |       1344 |      1000 | imagenet-1k  | EfficientNet | mobilenet_edgetpu_v2_m | 2024-07-29   |
| [mobilenetv2_100.ra_in1k](https://huggingface.co/timm/mobilenetv2_100.ra_in1k)                                       | 3.5M     | 300.8M  |          224 | True           |       1280 |      1000 | imagenet-1k  | EfficientNet | mobilenetv2_100        | 2022-12-13   |

## EfficientVit

2 models with model class `EfficientVit`.

| Name                                                                               | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model        | Architecture    | Created At   |
|:-----------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:-------------|:----------------|:-------------|
| [efficientvit_b2.r256_in1k](https://huggingface.co/timm/efficientvit_b2.r256_in1k) | 24.3M    | 2.1G    |          256 | True           |       2560 |      1000 | imagenet-1k | EfficientVit | efficientvit_b2 | 2023-08-18   |
| [efficientvit_b1.r256_in1k](https://huggingface.co/timm/efficientvit_b1.r256_in1k) | 9.1M     | 689.0M  |          256 | True           |       1600 |      1000 | imagenet-1k | EfficientVit | efficientvit_b1 | 2023-08-18   |

## EfficientVitLarge

1 model with model class `EfficientVitLarge`.

| Name                                                                               | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model             | Architecture    | Created At   |
|:-----------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:------------------|:----------------|:-------------|
| [efficientvit_l1.r224_in1k](https://huggingface.co/timm/efficientvit_l1.r224_in1k) | 52.7M    | 5.3G    |          224 | True           |       3200 |      1000 | imagenet-1k | EfficientVitLarge | efficientvit_l1 | 2023-11-21   |

## GhostNet

1 model with model class `GhostNet`.

| Name                                                                   | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model    | Architecture   | Created At   |
|:-----------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:---------|:---------------|:-------------|
| [ghostnetv2_100.in1k](https://huggingface.co/timm/ghostnetv2_100.in1k) | 4.9M     | 183.8M  |          224 | True           |       1280 |      1000 | imagenet-1k | GhostNet | ghostnetv2_100 | 2023-08-20   |

## HighPerfGpuNet

2 models with model class `HighPerfGpuNet`.

| Name                                                                                               | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model          | Architecture   | Created At   |
|:---------------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:---------------|:---------------|:-------------|
| [hgnetv2_b4.ssld_stage2_ft_in1k](https://huggingface.co/timm/hgnetv2_b4.ssld_stage2_ft_in1k)       | 19.8M    | 2.8G    |          224 | True           |       2048 |      1000 | imagenet-1k | HighPerfGpuNet | hgnetv2_b4     | 2024-02-12   |
| [hgnetv2_b3.ssld_stage1_in22k_in1k](https://huggingface.co/timm/hgnetv2_b3.ssld_stage1_in22k_in1k) | 16.3M    | 1.8G    |          224 | True           |       2048 |      1000 | imagenet-1k | HighPerfGpuNet | hgnetv2_b3     | 2024-02-12   |

## InceptionResnetV2

1 model with model class `InceptionResnetV2`.

| Name                                                                                   | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model             | Architecture        | Created At   |
|:---------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:------------------|:--------------------|:-------------|
| [inception_resnet_v2.tf_in1k](https://huggingface.co/timm/inception_resnet_v2.tf_in1k) | 55.8M    | 13.2G   |          299 | True           |       1536 |      1000 | imagenet-1k | InceptionResnetV2 | inception_resnet_v2 | 2023-04-25   |

## InceptionV4

1 model with model class `InceptionV4`.

| Name                                                                     | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model       | Architecture   | Created At   |
|:-------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:------------|:---------------|:-------------|
| [inception_v4.tf_in1k](https://huggingface.co/timm/inception_v4.tf_in1k) | 42.6M    | 12.3G   |          299 | True           |       1536 |      1000 | imagenet-1k | InceptionV4 | inception_v4   | 2023-04-25   |

## MetaFormer

3 models with model class `MetaFormer`.

| Name                                                                                               | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset      | Model      | Architecture   | Created At   |
|:---------------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:-------------|:-----------|:---------------|:-------------|
| [convformer_s36.sail_in1k_384](https://huggingface.co/timm/convformer_s36.sail_in1k_384)           | 40.0M    | 22.4G   |          384 | True           |        512 |      1000 | imagenet-1k  | MetaFormer | convformer_s36 | 2023-05-05   |
| [convformer_m36.sail_in22k_ft_in1k](https://huggingface.co/timm/convformer_m36.sail_in22k_ft_in1k) | 57.0M    | 12.8G   |          224 | True           |        576 |      1000 | imagenet-1k  | MetaFormer | convformer_m36 | 2023-05-05   |
| [caformer_s18.sail_in22k](https://huggingface.co/timm/caformer_s18.sail_in22k)                     | 69.0M    | 3.9G    |          224 | True           |        512 |     21841 | imagenet-22k | MetaFormer | caformer_s18   | 2023-05-05   |

## MobileNetV3

2 models with model class `MobileNetV3`.

| Name                                                                                       | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model       | Architecture   | Created At   |
|:-------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:------------|:---------------|:-------------|
| [fbnetv3_b.ra2_in1k](https://huggingface.co/timm/fbnetv3_b.ra2_in1k)                       | 6.6M     | 405.6M  |          224 | True           |       1984 |      1000 | imagenet-1k | MobileNetV3 | fbnetv3_b      | 2022-12-16   |
| [hardcorenas_f.miil_green_in1k](https://huggingface.co/timm/hardcorenas_f.miil_green_in1k) | 6.9M     | 340.7M  |          224 | True           |       1280 |      1000 | imagenet-1k | MobileNetV3 | hardcorenas_f  | 2023-04-21   |

## Nest

1 model with model class `Nest`.

| Name                                                                         | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model   | Architecture   | Created At   |
|:-----------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:--------|:---------------|:-------------|
| [nest_base_jx.goog_in1k](https://huggingface.co/timm/nest_base_jx.goog_in1k) | 67.0M    | 16.7G   |          224 | True           |        512 |      1000 | imagenet-1k | Nest    | nest_base_jx   | 2023-04-23   |

## NextViT

1 model with model class `NextViT`.

| Name                                                                     | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model   | Architecture   | Created At   |
|:-------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:--------|:---------------|:-------------|
| [nextvit_base.bd_in1k](https://huggingface.co/timm/nextvit_base.bd_in1k) | 44.8M    | 8.3G    |          224 | True           |       1024 |      1000 | imagenet-1k | NextViT | nextvit_base   | 2024-02-11   |

## RegNet

3 models with model class `RegNet`.

| Name                                                                                         | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model   | Architecture   | Created At   |
|:---------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:--------|:---------------|:-------------|
| [regnety_160.lion_in12k_ft_in1k](https://huggingface.co/timm/regnety_160.lion_in12k_ft_in1k) | 83.5M    | 15.9G   |          224 | True           |       3024 |      1000 | imagenet-1k | RegNet  | regnety_160    | 2023-03-21   |
| [regnetx_080.tv2_in1k](https://huggingface.co/timm/regnetx_080.tv2_in1k)                     | 39.5M    | 8.0G    |          224 | True           |       1920 |      1000 | imagenet-1k | RegNet  | regnetx_080    | 2023-03-21   |
| [regnetx_040.pycls_in1k](https://huggingface.co/timm/regnetx_040.pycls_in1k)                 | 22.0M    | 4.0G    |          224 | True           |       1360 |      1000 | imagenet-1k | RegNet  | regnetx_040    | 2023-03-21   |

## RepGhostNet

2 models with model class `RepGhostNet`.

| Name                                                                     | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model       | Architecture    | Created At   |
|:-------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:------------|:----------------|:-------------|
| [repghostnet_200.in1k](https://huggingface.co/timm/repghostnet_200.in1k) | 8.5M     | 559.5M  |          224 | True           |       1280 |      1000 | imagenet-1k | RepGhostNet | repghostnet_200 | 2023-08-19   |
| [repghostnet_050.in1k](https://huggingface.co/timm/repghostnet_050.in1k) | 1.0M     | 53.4M   |          224 | True           |       1280 |      1000 | imagenet-1k | RepGhostNet | repghostnet_050 | 2023-08-19   |

## ResNet

5 models with model class `ResNet`.

| Name                                                                     | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model   | Architecture   | Created At   |
|:-------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:--------|:---------------|:-------------|
| [resnet101d.ra2_in1k](https://huggingface.co/timm/resnet101d.ra2_in1k)   | 44.6M    | 10.6G   |          256 | True           |       2048 |      1000 | imagenet-1k | ResNet  | resnet101d     | 2023-04-05   |
| [resnetaa50.a1h_in1k](https://huggingface.co/timm/resnetaa50.a1h_in1k)   | 25.6M    | 5.2G    |          224 | True           |       2048 |      1000 | imagenet-1k | ResNet  | resnetaa50     | 2023-04-05   |
| [resnet50d.a1_in1k](https://huggingface.co/timm/resnet50d.a1_in1k)       | 25.6M    | 4.4G    |          224 | True           |       2048 |      1000 | imagenet-1k | ResNet  | resnet50d      | 2023-04-05   |
| [ecaresnet50t.a1_in1k](https://huggingface.co/timm/ecaresnet50t.a1_in1k) | 25.6M    | 4.3G    |          224 | True           |       2048 |      1000 | imagenet-1k | ResNet  | ecaresnet50t   | 2023-04-05   |
| [resnet34.a3_in1k](https://huggingface.co/timm/resnet34.a3_in1k)         | 21.8M    | 1.9G    |          160 | True           |        512 |      1000 | imagenet-1k | ResNet  | resnet34       | 2023-04-05   |

## ResNetV2

1 model with model class `ResNetV2`.

| Name                                                                                                       | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model    | Architecture       | Created At   |
|:-----------------------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:---------|:-------------------|:-------------|
| [resnetv2_101x1_bit.goog_in21k_ft_in1k](https://huggingface.co/timm/resnetv2_101x1_bit.goog_in21k_ft_in1k) | 2.0M     | 2.5M    |          448 | True           |       2048 |      1000 | imagenet-1k | ResNetV2 | resnetv2_101x1_bit | 2023-03-22   |

## RexNet

1 model with model class `RexNet`.

| Name                                                                                     | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model   | Architecture   | Created At   |
|:-----------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:--------|:---------------|:-------------|
| [rexnetr_300.sw_in12k_ft_in1k](https://huggingface.co/timm/rexnetr_300.sw_in12k_ft_in1k) | 34.7M    | 3.3G    |          224 | True           |       3840 |      1000 | imagenet-1k | RexNet  | rexnetr_300    | 2023-03-20   |

## SwinTransformer

1 model with model class `SwinTransformer`.

| Name                                                                                                     | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model           | Architecture                 | Created At   |
|:---------------------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:----------------|:-----------------------------|:-------------|
| [swin_base_patch4_window7_224.ms_in1k](https://huggingface.co/timm/swin_base_patch4_window7_224.ms_in1k) | 87.7M    | 15.2G   |          224 | True           |       1024 |      1000 | imagenet-1k | SwinTransformer | swin_base_patch4_window7_224 | 2023-03-18   |

## VisionTransformer

4 models with model class `VisionTransformer`.

| Name                                                                                                                           | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model             | Architecture                     | Created At   |
|:-------------------------------------------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:------------------|:---------------------------------|:-------------|
| [vit_base_r50_s16_384.orig_in21k_ft_in1k](https://huggingface.co/timm/vit_base_r50_s16_384.orig_in21k_ft_in1k)                 | 86.6M    | 49.5G   |          384 | True           |        768 |      1000 | imagenet-1k | VisionTransformer | vit_base_r50_s16_384             | 2022-12-23   |
| [vit_base_patch16_clip_384.laion2b_ft_in12k_in1k](https://huggingface.co/timm/vit_base_patch16_clip_384.laion2b_ft_in12k_in1k) | 86.4M    | 49.4G   |          384 | True           |        768 |      1000 | imagenet-1k | VisionTransformer | vit_base_patch16_clip_384        | 2022-11-11   |
| [vit_betwixt_patch16_reg1_gap_256.sbb_in1k](https://huggingface.co/timm/vit_betwixt_patch16_reg1_gap_256.sbb_in1k)             | 60.2M    | 15.3G   |          256 | True           |        640 |      1000 | imagenet-1k | VisionTransformer | vit_betwixt_patch16_reg1_gap_256 | 2024-05-10   |
| [vit_little_patch16_reg4_gap_256.sbb_in1k](https://huggingface.co/timm/vit_little_patch16_reg4_gap_256.sbb_in1k)               | 22.4M    | 5.7G    |          256 | True           |        320 |      1000 | imagenet-1k | VisionTransformer | vit_little_patch16_reg4_gap_256  | 2024-05-10   |

## Xcit

2 models with model class `Xcit`.

| Name                                                                                                   | Params   | Flops   |   Input Size | Can Classify   |   Features |   Classes | Dataset     | Model   | Architecture           | Created At   |
|:-------------------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:--------|:-----------------------|:-------------|
| [xcit_medium_24_p16_384.fb_dist_in1k](https://huggingface.co/timm/xcit_medium_24_p16_384.fb_dist_in1k) | 84.4M    | 46.5G   |          384 | True           |        512 |      1000 | imagenet-1k | Xcit    | xcit_medium_24_p16_384 | 2023-04-13   |
| [xcit_small_24_p16_224.fb_in1k](https://huggingface.co/timm/xcit_small_24_p16_224.fb_in1k)             | 47.6M    | 8.9G    |          224 | True           |        384 |      1000 | imagenet-1k | Xcit    | xcit_small_24_p16_224  | 2023-04-13   |