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Update README.md
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README.md
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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
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[technical report of jina-clip-v1](https://arxiv.org/abs/2405.20204)
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+
---
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2 |
+
library_name: transformers
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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 |
|