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@@ -1,124 +1,124 @@
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- ---
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- library_name: transformers
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- license: cc-by-nc-4.0
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- tags:
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- - xlm-roberta
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- - eva02
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- - clip
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- - feature-extraction
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- - sentence-similarity
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- - retrieval
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- - multimodal
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- - multi-modal
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- - crossmodal
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- - cross-modal
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- - mteb
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- - clip-benchmark
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- - vidore
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- - transformers
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- - sentence-transformers
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- - onnx
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- - safetensors
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- - transformers.js
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- language:
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- - multilingual
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- - af
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- - am
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- - ar
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- - as
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- - az
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- - be
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- - bg
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- - bn
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- - br
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- - bs
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- - ca
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- - cs
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- - cy
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- - da
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- - de
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- - el
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- - en
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- - eo
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- - es
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- - et
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- - eu
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- - fa
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- - fi
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- - fr
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- - fy
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- - ga
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- - gd
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- - gl
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- - gu
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- - ha
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- - he
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- - hi
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- - hr
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- - hu
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- - hy
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- - id
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- - is
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- - it
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- - ja
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- - jv
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- - ka
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- - kk
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- - km
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- - kn
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- - ko
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- - ku
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- - ky
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- - la
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- - lo
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- - lt
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- - lv
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- - mg
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- - mk
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- - ml
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- - mn
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- - mr
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- - ms
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- - my
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- - ne
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- - nl
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- - 'no'
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- - om
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- - or
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- - pa
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- - pl
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- - ps
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- - pt
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- - ro
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- - ru
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- - sa
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- - sd
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- - si
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- - sk
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- - sl
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- - so
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- - sq
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- - sr
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- - su
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- - sv
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- - sw
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- - ta
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- - te
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- - th
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- - tl
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- - tr
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- - ug
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- - uk
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- - ur
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- - uz
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- - vi
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- - xh
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- - yi
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- - zh
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- inference: false
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- base_model:
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- - jinaai/xlm-roberta-flash-implementation
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- ---
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  <br><br>
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@@ -179,7 +179,7 @@ CLIP-like models have established themselves as the backbone for general-purpose
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  ## Training, Data, Parameters
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- Please refer to our [technical report of jina-clip-v2](https://arxiv.org/abs/2412.08802) for he details of model and training procedure.
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  [technical report of jina-clip-v1](https://arxiv.org/abs/2405.20204)
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1
+ ---
2
+ library_name: transformers
3
+ license: cc-by-nc-4.0
4
+ tags:
5
+ - xlm-roberta
6
+ - eva02
7
+ - clip
8
+ - feature-extraction
9
+ - sentence-similarity
10
+ - retrieval
11
+ - multimodal
12
+ - multi-modal
13
+ - crossmodal
14
+ - cross-modal
15
+ - mteb
16
+ - clip-benchmark
17
+ - vidore
18
+ - transformers
19
+ - sentence-transformers
20
+ - onnx
21
+ - safetensors
22
+ - transformers.js
23
+ language:
24
+ - multilingual
25
+ - af
26
+ - am
27
+ - ar
28
+ - as
29
+ - az
30
+ - be
31
+ - bg
32
+ - bn
33
+ - br
34
+ - bs
35
+ - ca
36
+ - cs
37
+ - cy
38
+ - da
39
+ - de
40
+ - el
41
+ - en
42
+ - eo
43
+ - es
44
+ - et
45
+ - eu
46
+ - fa
47
+ - fi
48
+ - fr
49
+ - fy
50
+ - ga
51
+ - gd
52
+ - gl
53
+ - gu
54
+ - ha
55
+ - he
56
+ - hi
57
+ - hr
58
+ - hu
59
+ - hy
60
+ - id
61
+ - is
62
+ - it
63
+ - ja
64
+ - jv
65
+ - ka
66
+ - kk
67
+ - km
68
+ - kn
69
+ - ko
70
+ - ku
71
+ - ky
72
+ - la
73
+ - lo
74
+ - lt
75
+ - lv
76
+ - mg
77
+ - mk
78
+ - ml
79
+ - mn
80
+ - mr
81
+ - ms
82
+ - my
83
+ - ne
84
+ - nl
85
+ - 'no'
86
+ - om
87
+ - or
88
+ - pa
89
+ - pl
90
+ - ps
91
+ - pt
92
+ - ro
93
+ - ru
94
+ - sa
95
+ - sd
96
+ - si
97
+ - sk
98
+ - sl
99
+ - so
100
+ - sq
101
+ - sr
102
+ - su
103
+ - sv
104
+ - sw
105
+ - ta
106
+ - te
107
+ - th
108
+ - tl
109
+ - tr
110
+ - ug
111
+ - uk
112
+ - ur
113
+ - uz
114
+ - vi
115
+ - xh
116
+ - yi
117
+ - zh
118
+ inference: false
119
+ base_model:
120
+ - jinaai/xlm-roberta-flash-implementation
121
+ ---
122
 
123
  <br><br>
124
 
 
179
 
180
  ## Training, Data, Parameters
181
 
182
+ Please refer to our [technical report of jina-clip-v2](https://arxiv.org/abs/2412.08802) for the model and training details.
183
 
184
  [technical report of jina-clip-v1](https://arxiv.org/abs/2405.20204)
185