Hugging Face's logo

apple
/
aimv2-huge-patch14-448

Image Feature Extraction
Transformers
JAX
Safetensors
MLX
PyTorch
aimv2
feature-extraction
vision
custom_code
Eval Results
Model card Files Community
1
pcuenq HF staff commited on
Commit
5dd4392
·
verified ·
1 Parent(s): 6a3a497

AMLR license

Browse files
Files changed (1) hide show
  1. README.md +78 -78
README.md CHANGED
@@ -1,171 +1,171 @@
1
  ---
2
  library_name: transformers
3
- license: apple-ascl
4
  metrics:
5
  - accuracy
 
 
 
 
 
 
6
  model-index:
7
  - name: aimv2-huge-patch14-448
8
  results:
9
- - dataset:
 
 
 
10
  name: imagenet-1k
11
  type: imagenet-1k
12
  metrics:
13
- - name: Accuracy
14
- type: accuracy
15
  value: 88.6
 
16
  verified: false
17
- task:
18
- name: Classification
19
  type: classification
20
- - dataset:
 
21
  name: inaturalist-18
22
  type: inaturalist-18
23
  metrics:
24
- - name: Accuracy
25
- type: accuracy
26
  value: 82.8
 
27
  verified: false
28
- task:
29
- name: Classification
30
  type: classification
31
- - dataset:
 
32
  name: cifar10
33
  type: cifar10
34
  metrics:
35
- - name: Accuracy
36
- type: accuracy
37
  value: 99.4
 
38
  verified: false
39
- task:
40
- name: Classification
41
  type: classification
42
- - dataset:
 
43
  name: cifar100
44
  type: cifar100
45
  metrics:
46
- - name: Accuracy
47
- type: accuracy
48
  value: 93.6
 
49
  verified: false
50
- task:
51
- name: Classification
52
  type: classification
53
- - dataset:
 
54
  name: food101
55
  type: food101
56
  metrics:
57
- - name: Accuracy
58
- type: accuracy
59
  value: 97.0
 
60
  verified: false
61
- task:
62
- name: Classification
63
  type: classification
64
- - dataset:
 
65
  name: dtd
66
  type: dtd
67
  metrics:
68
- - name: Accuracy
69
- type: accuracy
70
  value: 88.9
 
71
  verified: false
72
- task:
73
- name: Classification
74
  type: classification
75
- - dataset:
 
76
  name: oxford-pets
77
  type: oxford-pets
78
  metrics:
79
- - name: Accuracy
80
- type: accuracy
81
  value: 96.8
 
82
  verified: false
83
- task:
84
- name: Classification
85
  type: classification
86
- - dataset:
 
87
  name: stanford-cars
88
  type: stanford-cars
89
  metrics:
90
- - name: Accuracy
91
- type: accuracy
92
  value: 96.5
 
93
  verified: false
94
- task:
95
- name: Classification
96
  type: classification
97
- - dataset:
 
98
  name: camelyon17
99
  type: camelyon17
100
  metrics:
101
- - name: Accuracy
102
- type: accuracy
103
  value: 93.4
 
104
  verified: false
105
- task:
106
- name: Classification
107
  type: classification
108
- - dataset:
 
109
  name: patch-camelyon
110
  type: patch-camelyon
111
  metrics:
112
- - name: Accuracy
113
- type: accuracy
114
  value: 89.6
 
115
  verified: false
116
- task:
117
- name: Classification
118
  type: classification
119
- - dataset:
 
120
  name: rxrx1
121
  type: rxrx1
122
  metrics:
123
- - name: Accuracy
124
- type: accuracy
125
  value: 7.8
 
126
  verified: false
127
- task:
128
- name: Classification
129
  type: classification
130
- - dataset:
 
131
  name: eurosat
132
  type: eurosat
133
  metrics:
134
- - name: Accuracy
135
- type: accuracy
136
  value: 98.7
 
137
  verified: false
138
- task:
139
- name: Classification
140
  type: classification
141
- - dataset:
 
142
  name: fmow
143
  type: fmow
144
  metrics:
145
- - name: Accuracy
146
- type: accuracy
147
  value: 64.8
 
148
  verified: false
149
- task:
150
- name: Classification
151
  type: classification
152
- - dataset:
 
153
  name: domainnet-infographic
154
  type: domainnet-infographic
155
  metrics:
156
- - name: Accuracy
157
- type: accuracy
158
  value: 74.5
 
159
  verified: false
160
- task:
161
- name: Classification
162
- type: classification
163
- pipeline_tag: image-feature-extraction
164
- tags:
165
- - vision
166
- - image-feature-extraction
167
- - mlx
168
- - pytorch
169
  ---
170
  # Introduction
171
  [[`AIMv2 Paper`](https://arxiv.org/abs/2411.14402)] [[`BibTeX`](#citation)]
 
1
  ---
2
  library_name: transformers
3
+ license: apple-amlr
4
  metrics:
5
  - accuracy
6
+ pipeline_tag: image-feature-extraction
7
+ tags:
8
+ - vision
9
+ - image-feature-extraction
10
+ - mlx
11
+ - pytorch
12
  model-index:
13
  - name: aimv2-huge-patch14-448
14
  results:
15
+ - task:
16
+ type: classification
17
+ name: Classification
18
+ dataset:
19
  name: imagenet-1k
20
  type: imagenet-1k
21
  metrics:
22
+ - type: accuracy
 
23
  value: 88.6
24
+ name: Accuracy
25
  verified: false
26
+ - task:
 
27
  type: classification
28
+ name: Classification
29
+ dataset:
30
  name: inaturalist-18
31
  type: inaturalist-18
32
  metrics:
33
+ - type: accuracy
 
34
  value: 82.8
35
+ name: Accuracy
36
  verified: false
37
+ - task:
 
38
  type: classification
39
+ name: Classification
40
+ dataset:
41
  name: cifar10
42
  type: cifar10
43
  metrics:
44
+ - type: accuracy
 
45
  value: 99.4
46
+ name: Accuracy
47
  verified: false
48
+ - task:
 
49
  type: classification
50
+ name: Classification
51
+ dataset:
52
  name: cifar100
53
  type: cifar100
54
  metrics:
55
+ - type: accuracy
 
56
  value: 93.6
57
+ name: Accuracy
58
  verified: false
59
+ - task:
 
60
  type: classification
61
+ name: Classification
62
+ dataset:
63
  name: food101
64
  type: food101
65
  metrics:
66
+ - type: accuracy
 
67
  value: 97.0
68
+ name: Accuracy
69
  verified: false
70
+ - task:
 
71
  type: classification
72
+ name: Classification
73
+ dataset:
74
  name: dtd
75
  type: dtd
76
  metrics:
77
+ - type: accuracy
 
78
  value: 88.9
79
+ name: Accuracy
80
  verified: false
81
+ - task:
 
82
  type: classification
83
+ name: Classification
84
+ dataset:
85
  name: oxford-pets
86
  type: oxford-pets
87
  metrics:
88
+ - type: accuracy
 
89
  value: 96.8
90
+ name: Accuracy
91
  verified: false
92
+ - task:
 
93
  type: classification
94
+ name: Classification
95
+ dataset:
96
  name: stanford-cars
97
  type: stanford-cars
98
  metrics:
99
+ - type: accuracy
 
100
  value: 96.5
101
+ name: Accuracy
102
  verified: false
103
+ - task:
 
104
  type: classification
105
+ name: Classification
106
+ dataset:
107
  name: camelyon17
108
  type: camelyon17
109
  metrics:
110
+ - type: accuracy
 
111
  value: 93.4
112
+ name: Accuracy
113
  verified: false
114
+ - task:
 
115
  type: classification
116
+ name: Classification
117
+ dataset:
118
  name: patch-camelyon
119
  type: patch-camelyon
120
  metrics:
121
+ - type: accuracy
 
122
  value: 89.6
123
+ name: Accuracy
124
  verified: false
125
+ - task:
 
126
  type: classification
127
+ name: Classification
128
+ dataset:
129
  name: rxrx1
130
  type: rxrx1
131
  metrics:
132
+ - type: accuracy
 
133
  value: 7.8
134
+ name: Accuracy
135
  verified: false
136
+ - task:
 
137
  type: classification
138
+ name: Classification
139
+ dataset:
140
  name: eurosat
141
  type: eurosat
142
  metrics:
143
+ - type: accuracy
 
144
  value: 98.7
145
+ name: Accuracy
146
  verified: false
147
+ - task:
 
148
  type: classification
149
+ name: Classification
150
+ dataset:
151
  name: fmow
152
  type: fmow
153
  metrics:
154
+ - type: accuracy
 
155
  value: 64.8
156
+ name: Accuracy
157
  verified: false
158
+ - task:
 
159
  type: classification
160
+ name: Classification
161
+ dataset:
162
  name: domainnet-infographic
163
  type: domainnet-infographic
164
  metrics:
165
+ - type: accuracy
 
166
  value: 74.5
167
+ name: Accuracy
168
  verified: false
 
 
 
 
 
 
 
 
 
169
  ---
170
  # Introduction
171
  [[`AIMv2 Paper`](https://arxiv.org/abs/2411.14402)] [[`BibTeX`](#citation)]