Dataset Viewer
Auto-converted to Parquet Duplicate
image
unknown
text
string
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 2, 32, 0, 0, 0, 96, 8, 0, 0, 0, 0, 1, 37, 150, 133, 0, 0, 14, 155, 73, 68, 65, 84, 120, 156, 237, 93, 237, 153, 178, 60, 19, 61, 251, 94, 111,...
E _ { n } = - { \frac { m _ { e } e ^ { 4 } } { 2 ( 4 \pi \varepsilon _ { 0 } \hbar ) ^ { 2 } } } ~ { \frac { 1 } { n ^ { 2 } } } = - { \frac { 1 3 . 6 ~ { \mathrm { e V } } } { n ^ { 2 } } } .
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 32, 0, 0, 0, 32, 8, 0, 0, 0, 0, 86, 17, 37, 40, 0, 0, 0, 112, 73, 68, 65, 84, 120, 156, 99, 252, 207, 128, 31, 48, 17, 144, 31, 38, 10, 8...
\equiv
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 1, 192, 0, 0, 0, 96, 8, 0, 0, 0, 0, 175, 37, 253, 245, 0, 0, 11, 14, 73, 68, 65, 84, 120, 156, 237, 93, 239, 157, 171, 160, 18, 61, 247, 253, ...
C _ { a } ( t ) = \sum _ { k } ^ { \infin } c _ { a k } \exp ( - \nu _ { a k } t )
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 32, 0, 0, 0, 32, 8, 0, 0, 0, 0, 86, 17, 37, 40, 0, 0, 0, 157, 73, 68, 65, 84, 120, 156, 237, 146, 65, 17, 195, 32, 16, 69, 127, 58, 53, 1...
C _ { 0 }
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 1, 128, 0, 0, 0, 32, 8, 0, 0, 0, 0, 62, 199, 240, 57, 0, 0, 5, 89, 73, 68, 65, 84, 120, 156, 229, 90, 237, 145, 164, 32, 16, 125, 123, 117, 9,...
- 0 . 2 5 \gamma \le \Delta \omega \le 0 . 2 5 \gamma
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 96, 0, 0, 0, 32, 8, 0, 0, 0, 0, 200, 171, 34, 136, 0, 0, 1, 106, 73, 68, 65, 84, 120, 156, 237, 86, 193, 113, 131, 48, 16, 92, 50, 105, 64,...
l = 2
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 1, 160, 0, 0, 0, 160, 8, 0, 0, 0, 0, 111, 42, 231, 49, 0, 0, 16, 206, 73, 68, 65, 84, 120, 156, 237, 93, 205, 177, 171, 60, 182, 93, 183, 235, ...
\hat { G } _ { e } = J ^ { - 1 } \left \{ \begin{array} { c } { \overline { \rho } W } \\ { \overline { \rho } \tilde { u } W + \overline { p } \zeta _ { x } } \\ { \overline { \rho } \tilde { v } W + \overline { p } \zeta _ { y } } \\ { \overline { \rho } \tilde { w } W + \overline { p } \zeta _ { z } } \\ { \left ( \...
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 1, 160, 0, 0, 0, 224, 8, 0, 0, 0, 0, 96, 114, 237, 93, 0, 0, 13, 102, 73, 68, 65, 84, 120, 156, 237, 157, 63, 114, 235, 186, 21, 198, 191, 155, ...
\left ( \begin{array} { l l l } { \rho _ { 1 1 } } & { \cdots } & { \rho _ { 1 d } } \\ { \vdots } & { \ddots } & { \vdots } \\ { \rho _ { d 1 } } & { \cdots } & { \rho _ { d d } } \end{array} \right ) \Longrightarrow \left ( \begin{array} { l } { \rho _ { 1 1 } } \\ { \rho _ { 1 2 } } \\ { \vdots } \\ { \rho _ { 1 d }...
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 160, 0, 0, 0, 96, 8, 0, 0, 0, 0, 191, 76, 38, 69, 0, 0, 3, 219, 73, 68, 65, 84, 120, 156, 237, 154, 209, 117, 163, 58, 16, 134, 127, 223, 1...
\begin{array} { r l } { 0 } & { { } = \frac { \partial \tilde { H } } { \partial \kappa } } \end{array}
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 32, 0, 0, 0, 32, 8, 0, 0, 0, 0, 86, 17, 37, 40, 0, 0, 0, 120, 73, 68, 65, 84, 120, 156, 99, 252, 207, 128, 31, 48, 17, 144, 31, 85, 64, 1...
\vec { e }
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 1, 32, 0, 0, 0, 64, 8, 0, 0, 0, 0, 159, 107, 245, 178, 0, 0, 6, 167, 73, 68, 65, 84, 120, 156, 237, 90, 235, 145, 163, 188, 18, 61, 123, 107, ...
{ \frac { 1 } { 2 } } { \frac { \coth ( \pi w ) } { \pi w } } - { \frac { 1 } { 2 } } { \frac { 1 } { z ^ { 2 } } } = \sum _ { n = 1 } ^ { \infin } { \frac { 1 } { n ^ { 2 } + w ^ { 2 } } }
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 2, 96, 0, 0, 0, 32, 8, 0, 0, 0, 0, 144, 199, 155, 73, 0, 0, 7, 1, 73, 68, 65, 84, 120, 156, 237, 92, 219, 149, 163, 58, 16, 172, 157, 179, 9, ...
t _ { 0 } = 0 , ~ t _ { 1 } = \delta t , ~ \cdots , t _ { k } = k \delta t , ~ \cdots , ~ t _ { n } = n \delta t
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 1, 128, 0, 0, 0, 96, 8, 0, 0, 0, 0, 49, 159, 250, 85, 0, 0, 10, 110, 73, 68, 65, 84, 120, 156, 237, 93, 225, 153, 171, 160, 18, 61, 251, 190, ...
G ( s , t ) = \sum _ { x = 0 } s ^ { x } p ( x , t ) ,
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 1, 160, 0, 0, 0, 64, 8, 0, 0, 0, 0, 121, 110, 252, 179, 0, 0, 8, 108, 73, 68, 65, 84, 120, 156, 237, 91, 219, 149, 227, 170, 18, 221, 190, 235, ...
\begin{array} { r } { K \equiv \frac { 1 } { | \hat { e } _ { \perp } { \cdot } \partial _ { \Delta \lambda } \Delta \hat { e } ( 0 ) | ^ { 2 } } \operatorname* { l i m } _ { \mathrm { R e } ( \Delta \lambda ) \rarr 0 } \frac { | \lambda _ { 0 } | ^ { 2 } \mathrm { R e } \lambda _ { 1 } + | \lambda _ { 1 } | ^ { 2 } \m...
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 1, 64, 0, 0, 0, 128, 8, 0, 0, 0, 0, 95, 100, 239, 118, 0, 0, 7, 181, 73, 68, 65, 84, 120, 156, 237, 156, 219, 153, 163, 56, 16, 133, 207, 236, ...
T = \frac { 1 } { 4 \pi } ~ \frac { r _ { + } - r _ { - } } { r _ { + } ^ { 2 } - \S ^ { 2 } } ~ .
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 32, 0, 0, 0, 32, 8, 0, 0, 0, 0, 86, 17, 37, 40, 0, 0, 0, 166, 73, 68, 65, 84, 120, 156, 237, 146, 65, 17, 194, 48, 16, 69, 127, 112, 16, ...
1 / r
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 1, 75, 0, 0, 0, 104, 8, 2, 0, 0, 0, 247, 154, 69, 229, 0, 0, 112, 168, 73, 68, 65, 84, 120, 156, 205, 189, 199, 146, 36, 57, 178, 32, 168, 170, ...
\frac { 2 } { \sin A } = \frac { 1 } { \sin C }
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 32, 0, 0, 0, 32, 8, 0, 0, 0, 0, 86, 17, 37, 40, 0, 0, 0, 239, 73, 68, 65, 84, 120, 156, 237, 147, 65, 117, 196, 32, 0, 68, 127, 250, 214, ...
R e
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 2, 64, 0, 0, 0, 64, 8, 0, 0, 0, 0, 215, 110, 151, 195, 0, 0, 11, 84, 73, 68, 65, 84, 120, 156, 237, 93, 237, 153, 179, 160, 18, 61, 123, 159, ...
\left \| x \right \| _ { p } = { \bigg ( } \sum _ { i \in \mathbb { N } } \left | x _ { i } \right | ^ { p } { \bigg ) } ^ { 1 / p } { \mathrm { ~ a n d } } ~ \left \| f \right \| _ { p , X } = { \bigg ( } \int _ { X } \left | f ( x ) \right | ^ { p } ~ \mathrm { d } x { \bigg ) } ^ { 1 / p }
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 2, 96, 0, 0, 0, 64, 8, 0, 0, 0, 0, 152, 51, 148, 19, 0, 0, 9, 171, 73, 68, 65, 84, 120, 156, 237, 157, 237, 149, 179, 42, 23, 134, 239, 121, 2...
E _ { \pm } \approx S _ { \pm } / [ 1 - i ( Y _ { \pm } + 2 Y _ { \mp } - \Delta _ { \pm } ) ]
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 160, 0, 0, 0, 32, 8, 0, 0, 0, 0, 176, 20, 44, 41, 0, 0, 2, 243, 73, 68, 65, 84, 120, 156, 205, 152, 219, 153, 155, 48, 16, 70, 207, 230, 75...
\Omega \rarr \infin
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 173, 0, 0, 0, 66, 8, 0, 0, 0, 0, 0, 214, 9, 200, 0, 0, 1, 184, 73, 68, 65, 84, 120, 156, 237, 153, 209, 146, 195, 32, 8, 69, 161, 211, 255,...
p = p _ { e }
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 128, 0, 0, 0, 64, 8, 0, 0, 0, 0, 247, 189, 32, 163, 0, 0, 3, 169, 73, 68, 65, 84, 120, 156, 197, 89, 221, 153, 163, 32, 20, 61, 217, 111, 2...
F _ { i j } = { \frac { \partial f _ { i } } { \partial v _ { j } } } .
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 96, 0, 0, 0, 32, 8, 0, 0, 0, 0, 200, 171, 34, 136, 0, 0, 1, 134, 73, 68, 65, 84, 120, 156, 237, 149, 219, 113, 131, 48, 16, 69, 47, 153, 52...
\tau _ { m a x _ { 1 } } = 6 . 7
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 2, 224, 0, 0, 0, 224, 8, 0, 0, 0, 0, 103, 42, 140, 252, 0, 0, 32, 207, 73, 68, 65, 84, 120, 156, 237, 157, 63, 146, 171, 176, 150, 198, 191, 158...
\left \{ \begin{array} { r c l } { \tilde { m } _ { n } ^ { \pm } } & { = } & { \frac { 2 n - 1 } { R } \pm m _ { q } ( \phi _ { H } ) } \\ { m _ { n } ^ { \pm } } & { = } & { m _ { q } ( \phi _ { H } ) \pm \frac { 2 n } { R } } \\ { m _ { 0 } } & { = } & { m _ { q } ( \phi _ { H } ) = \frac { 2 } { \pi R } \mathrm { a...
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 1, 0, 0, 0, 0, 64, 8, 0, 0, 0, 0, 208, 54, 246, 98, 0, 0, 6, 213, 73, 68, 65, 84, 120, 156, 237, 90, 239, 125, 227, 40, 16, 125, 123, 191, 107...
X \sim { \mathcal { B } } e ( \alpha , \beta )
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 4, 0, 0, 0, 0, 128, 8, 0, 0, 0, 0, 176, 137, 68, 148, 0, 0, 35, 46, 73, 68, 65, 84, 120, 156, 237, 125, 189, 145, 235, 190, 147, 237, 185, 91, ...
\begin{array} { r l } { \mathbb { P } ( \mathcal { L } _ { < } ( \Pi _ { x , t } ^ { ( \lambda ) } ) } & { > ( 1 + \varepsilon ) ( 2 \sqrt { x t \lambda } - x \lambda ) ) \le \exp ( - g ( \varepsilon ) ( \sqrt { x t \lambda } - x \lambda ) ) , } \\ { \mathbb { P } ( \mathcal { L } _ { < } ( \Pi _ { x , t } ^ { ( \lambd...
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 2, 96, 0, 0, 0, 64, 8, 0, 0, 0, 0, 152, 51, 148, 19, 0, 0, 9, 190, 73, 68, 65, 84, 120, 156, 237, 156, 235, 153, 179, 56, 18, 133, 207, 236, 1...
\begin{array} { r l } { \sum _ { i \in V } D _ { i i } ~ x _ { i } ^ { ( 1 ) } } & { { } = \sum _ { i \in V } D _ { i i } \cdot \frac { 1 } { D _ { i i } } \sum _ { j \in V } W _ { i j } ~ x _ { j } ^ { ( 0 ) } \cdot \left ( 1 + \sigma _ { \lambda ; i } ( \mathbf { x } ^ { ( 0 ) } ) \right ) } \end{array}
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 2, 224, 0, 0, 0, 192, 8, 0, 0, 0, 0, 96, 134, 137, 202, 0, 0, 29, 47, 73, 68, 65, 84, 120, 156, 237, 157, 237, 153, 179, 174, 243, 246, 207, 223...
\begin{array} { r l } { G _ { n _ { \| } n _ { \| } } ^ { R } } & { = \frac { \chi \Gamma ( i \omega - \tilde { D } _ { \psi } k ^ { 2 } - \tilde { \Omega } ) - \chi \omega _ { 0 } ^ { 2 } } { \big ( i \omega - D _ { \ell } k ^ { 2 } - \Gamma \big ) \big ( i \omega - \tilde { D } _ { \psi } k ^ { 2 } - \tilde { \Omega ...
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 128, 0, 0, 0, 64, 8, 0, 0, 0, 0, 247, 189, 32, 163, 0, 0, 2, 230, 73, 68, 65, 84, 120, 156, 237, 152, 219, 149, 155, 48, 16, 134, 63, 231, ...
5 { ~ } 2 0 5
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 1, 128, 0, 0, 0, 96, 8, 0, 0, 0, 0, 49, 159, 250, 85, 0, 0, 7, 136, 73, 68, 65, 84, 120, 156, 237, 157, 209, 153, 171, 42, 20, 133, 151, 247, ...
m ^ { 4 } \int D [ C ] ~ | \Psi [ C ] | ^ { 2 } = 1 .
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 3, 160, 0, 0, 0, 96, 8, 0, 0, 0, 0, 38, 174, 64, 68, 0, 0, 20, 79, 73, 68, 65, 84, 120, 156, 237, 93, 235, 121, 171, 60, 179, 93, 251, 60, 167...
\begin{array} { r l } { \vec { v _ { i } } ^ { 0 } } & { { } = \frac { \Gamma } { 2 \pi } \sum _ { i \neq j } ^ { N _ { v } } \kappa _ { j } \hat { z } \times \frac { \vec { r } _ { i } - \vec { r } _ { j } } { \left | \vec { r } _ { i } - \vec { r } _ { j } \right | ^ { 2 } } + \frac { 1 } { 2 } \left ( \frac { \Gamma...
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 64, 0, 0, 0, 32, 8, 0, 0, 0, 0, 135, 246, 33, 88, 0, 0, 1, 103, 73, 68, 65, 84, 120, 156, 213, 149, 221, 117, 195, 32, 12, 133, 111, 122, 1...
\Im \mathrm { E }
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 96, 0, 0, 0, 32, 8, 0, 0, 0, 0, 200, 171, 34, 136, 0, 0, 1, 106, 73, 68, 65, 84, 120, 156, 181, 150, 91, 113, 195, 48, 16, 69, 143, 59, 37,...
\mu = 1
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 32, 0, 0, 0, 64, 8, 0, 0, 0, 0, 94, 229, 42, 114, 0, 0, 1, 88, 73, 68, 65, 84, 120, 156, 237, 149, 193, 113, 131, 48, 16, 69, 191, 25, 55, ...
h _ { j }
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 32, 0, 0, 0, 32, 8, 0, 0, 0, 0, 86, 17, 37, 40, 0, 0, 1, 25, 73, 68, 65, 84, 120, 156, 109, 146, 81, 113, 195, 48, 16, 68, 95, 50, 33, 32...
h
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 118, 0, 0, 0, 49, 8, 2, 0, 0, 0, 128, 152, 202, 146, 0, 0, 23, 8, 73, 68, 65, 84, 120, 156, 165, 91, 201, 118, 236, 56, 114, 141, 8, 0, 28,...
\frac { 2 } { 3 } = 6 : x
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 64, 0, 0, 0, 32, 8, 0, 0, 0, 0, 135, 246, 33, 88, 0, 0, 0, 254, 73, 68, 65, 84, 120, 156, 237, 148, 225, 141, 131, 48, 12, 133, 191, 158, 1...
\alpha _ { i } > 0 . 5
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 1, 160, 0, 0, 0, 64, 8, 0, 0, 0, 0, 121, 110, 252, 179, 0, 0, 7, 141, 73, 68, 65, 84, 120, 156, 237, 156, 237, 153, 170, 58, 20, 133, 151, 247, ...
\begin{array} { r } { \left \| \widetilde { \Lambda } ^ { - 1 } \widetilde { V } ^ { * } \omega ^ { ( - ) } \right \| _ { w ^ { k - 1 } } = \left \| \beta ^ { ( - ) } \right \| _ { w ^ { k - 1 } } . } \end{array}
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 2, 160, 0, 0, 0, 64, 8, 0, 0, 0, 0, 224, 140, 154, 178, 0, 0, 11, 167, 73, 68, 65, 84, 120, 156, 237, 93, 237, 153, 171, 160, 214, 93, 231, 125,...
( 9 + u _ { 0 } ^ { 3 } ) + ( 6 + u _ { 1 } ^ { 3 } ) \alpha + ( 3 + u _ { 2 } ^ { 3 } ) \alpha ^ { 2 } = 0
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 1, 0, 0, 0, 0, 32, 8, 0, 0, 0, 0, 216, 194, 249, 56, 0, 0, 2, 66, 73, 68, 65, 84, 120, 156, 237, 152, 219, 145, 163, 48, 16, 69, 143, 183, 38,...
\left ( S ( | \mathbf { k } _ { 1 } + \mathbf { k } _ { 2 } | ) + S ( | \mathbf { k } _ { 1 } + \mathbf { k } _ { 3 } | ) + S ( | \mathbf { k } _ { 2 } + \mathbf { k } _ { 3 } | ) \right ) < 2
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 212, 0, 0, 0, 85, 8, 2, 0, 0, 0, 190, 80, 93, 50, 0, 0, 98, 137, 73, 68, 65, 84, 120, 156, 133, 253, 231, 178, 36, 73, 178, 38, 136, 41, 49...
( 3 ) y = \frac { 1 } { 4 }
[ 137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 64, 0, 0, 0, 32, 8, 0, 0, 0, 0, 135, 246, 33, 88, 0, 0, 1, 235, 73, 68, 65, 84, 120, 156, 157, 149, 93, 153, 164, 48, 16, 69, 207, 244, 183...
\Delta n ^ { a }
End of preview. Expand in Data Studio
README.md exists but content is empty.
Downloads last month
7

Models trained or fine-tuned on alephpi/UniMER-Train