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... | sample_000044 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
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"frequency_stats": {
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"frequency_distribution":... | sample_000045 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
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},
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"frequency_stats": {
"avg_frequency": 1,
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"freque... | sample_000046 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
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},
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},
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"frequency_stats": {
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"frequency_distribution": {
... | sample_000047 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
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},
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"frequency_stats": {
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"frequency_distribution":... | sample_000048 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
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},
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},
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"frequency_stats": {
"avg_frequency": 1,
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"frequen... | sample_000049 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
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"frequency_stats": {
"avg_frequency": 2.7274392625528465,
"frequency_distribution":... | sample_000050 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
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},
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"frequency_distribution": {... | sample_000051 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
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},
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"frequency_stats": {
"avg_frequency": 5.825169735492953,
"frequency_distribution":... | sample_000052 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
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"frequency_stats": {
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"frequency_distribution": {
... | sample_000053 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
"color_scheme": "random",
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},
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"fixed_params": {
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"frequency_stats": {
"avg_frequency": 3.3787345388189394,
"frequency_distribution":... | sample_000054 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
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},
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"fixed_params": {
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},
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"frequency_stats": {
"avg_frequency": 1,
"frequency_distribution": {
"frequency... | sample_000055 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
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},
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"fixed_params": {
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},
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"frequency_stats": {
"avg_frequency": 6.093117901710276,
"frequency_distribution":... | sample_000056 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
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},
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},
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"frequency_stats": {
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"frequen... | sample_000057 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
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},
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"frequency_distribution": {
... | sample_000058 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
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},
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"duration": 100,
"height": 32,
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"frequency_stats": {
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"frequency_distribution": {
... | sample_000059 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
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"fixed_params": {
"duration": 100,
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"width": 32
},
"frames": 60,
"frequency_stats": {
"avg_frequency": 10.847376308600108,
"frequency_distribution":... | sample_000060 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
"color_scheme": "ocean",
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},
"duration_ms": 100,
"fixed_params": {
"duration": 100,
"height": 32,
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"frequency_stats": {
"avg_frequency": 3.9618467083550906,
"frequency_distribution": ... | sample_000061 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
"color_scheme": "ocean",
"dimensions": {
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},
"duration_ms": 100,
"fixed_params": {
"duration": 100,
"height": 32,
"num_frames": 60,
"width": 32
},
"frames": 60,
"frequency_stats": {
"avg_frequency": 3.714326327121535,
"frequency_distribution": {... | sample_000062 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
"color_scheme": "random",
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"width": 32
},
"duration_ms": 100,
"fixed_params": {
"duration": 100,
"height": 32,
"num_frames": 60,
"width": 32
},
"frames": 60,
"frequency_stats": {
"avg_frequency": 5.937225391269158,
"frequency_distribution": ... | sample_000063 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
"color_scheme": "fire",
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"height": 32,
"width": 32
},
"duration_ms": 100,
"fixed_params": {
"duration": 100,
"height": 32,
"num_frames": 60,
"width": 32
},
"frames": 60,
"frequency_stats": {
"avg_frequency": 5.7600720380379045,
"frequency_distribution": {... | sample_000064 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar | |
{
"color_scheme": "aurora",
"dimensions": {
"height": 32,
"width": 32
},
"duration_ms": 100,
"fixed_params": {
"duration": 100,
"height": 32,
"num_frames": 60,
"width": 32
},
"frames": 60,
"frequency_stats": {
"avg_frequency": 2.008354602297219,
"frequency_distribution": ... | sample_000065 | hf://datasets/axiomflow42/gradienttile-100k@adaa58e7557b49e436d5065e92f83c64f5bf69bb/shard_000000.tar |
End of preview. Expand in Data Studio
A large-scale dataset of 100K procedurally generated animated GIFs featuring mathematical patterns, fractals, and artistic visualizations.
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