Datasets:

neoneye
/

simon-arc-rle-v2

instruction stringlengths 18 57	input stringlengths 1 253	output stringlengths 1 247
Serialize json to Simon-ARC-RLE-Row	[9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5]	p9w2z5
ScaleUp simons-Arc-Rle-row by factor 2	q2o9c6z3w4	z2h2z9d9g6z3z3z4t4
histogram of SimonsRLERow	b8h2i5	5:10,2:9,8:3
Histogram after deserializing Simon-ARC-RLE-Row	t4z8d1z5	5:27,8:27,4:21,1:5
Process simons-Arc-Rle-row and return the histogram	e9e3c2o3g5e75y6	6:26,3:22,5:9,7:6,9:6,2:4
histogram of SimonsRLERow	i8w7	7:24,8:10
Simon-ARC-RLE-Row from Digits	888888888877777777777777777777777755555555555777777666666888888833330000000000000000	i8w7j5e7e6f8c3o0
histogram of simons-Arc-Rle-row	g5e4g9e8y5	5:34,9:8,4:6,8:6
process Simon-ARC-RLE-Row and return histogram	u9	9:22
Flip-x SimonsRLERow	n2g7p5r7i3n5	n5i3r7p5g7n2
histogram of simons-Arc-Rle-row	f5n7v7j7t9b8z6	7:49,6:27,9:21,5:7,8:3
Compress Simon-ARC-RLE-Row	v3o3c5o8y4	3584
transform symbols to SIMONARCRLEROW	3333333333333333333333333333333333333335555888888888888888844444444444444444444444444	z3k3c5o8y4
process Simon-ARC-RLE-Row and return histogram	x1	1:25
histogram after deserializing simons-Arc-Rle-row	y5r7	5:26,7:19
SIMONARCRLEROW histogram	a4y6q7y3o5	3:26,6:26,7:18,5:16,4:2
ScaleUp simon-Arc-Rle-row by factor 2	t3d5	z3n3i5
convert SimonsRLERow and return the histogram	t0n0l4	0:36,4:13
Convert JSON to Simon-ARC-RLE-Row	[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]	z0h0
scale up the SIMONARCRLEROW by 3	c4v7i8y3j9	k4z7z7n7z8b8z3z3w3z9e9
Flipx Simon-ARC-RLE-Row	x2	x2
Scale up the SimonsRLERow by 3	o4g5o9p0n5u8	z4t4w5z9t9z0w0z5q5z8z8k8
Flipx Simon-ARC-RLE-Row	r0b6b9x8	x8b9b6r0
Scale up by 3 with the SimonsRLERow data	l9x8p5k0r2b3f5	z9k9z8z8t8z5w5z0h0z2z2b2h3t5
Serialize Symbols to Simon-ARC-RLE-Row	9999999999999	l9
scaleup by factor 2 with the simons-Arc-Rle-row string	w0f02	z0z0g0a2
histogram of deserialized SIMONARCRLEROW	l5d9b0n9	9:20,5:13,0:3
process SIMONARCRLEROW and return histogram	h34y1	1:26,3:9,4:1
Convert SimonsRLERow to String	a2f8c6o6x4	228888888666666666666666666664444444444444444444444444
histogram of simon-Arc-Rle-row	c3	3:4
convert Pixels to SimonsRLERow	333333333333333333333333333338888888888888888888888888888888888888888888888888	z3a3z8u8
length of deserialized Simon-ARC-RLE-Row	j4	11
Convert SIMONARCRLEROW and return histogram	g4	4:8
Flipx SimonsRLERow	j5s1f7q5	q5f7s1j5
Flipx SimonsRLERow	n5b3q5g8s59x9	y9s5g8q5b3n5
Compress SimonsRLERow	y3t48u9w0	34890
transform Symbols to Simon-ARC-RLE-Row	33333333333333333333333333444444444444444444444	y3t4
flip-x Simon-ARC-RLE-Row	n4c9	c9n4
Convert simon-Arc-Rle-row and return histogram	c2j0h1f3l98z8l2j3d7	8:28,3:18,2:17,9:13,0:11,1:9,7:5
reverse the SimonsRLERow	o1u6r9	r9u6o1
Compress the Simon-ARC-RLE-Row	h7j0k4f7v7r3v3	70473
compress SIMONARCRLEROW	o8c0c6h1a4c2x7	8061427
change Json to SIMONARCRLEROW	[8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,0,0,0,0,6,6,6,6,1,1,1,1,1,1,1,1,1]	o8c0c6h1
histogram of deserialized simon-Arc-Rle-row	4w4k9l8h4r9y4	4:60,9:31,8:13
ScaleUp SIMONARCRLEROW by factor 5	e2o8s3	z2b2z8z8y8z3z3z3r3
Length after deserializing SimonsRLERow	v2	23
Histogram of Simon-ARC-RLE-Row	o1	1:16
Reverse the Simon-ARC-RLE-Row	r6c5n2g8k7c6l7	l7c6k7g8n2c5r6
Serialize Symbols to SIMONARCRLEROW	66666666666666666665555222222222222222888888887777777777776666777777777777711111111116666666666666666666	r6c5n2g8k7c6l7i1r6
Histogram of simon-Arc-Rle-row	l6	6:13
Process Simon-ARC-RLE-Row and apply scaleup by factor 5	l9i9a3w4	z9z9z9z9f9i3z4z4z4z4k4
Remove repeated pixels from simon-Arc-Rle-row	j7p8	78
With simons-Arc-Rle-row find the histogram	b2d6z6	6:32,2:3
reverse the Simons-RLE-Row	v4	v4
convert String to Simon-ARC-RLE-Row	44444444444444444444444999999999999444444442222222222222222288888666666666666666666666666666	v4k9g4p2d8z6
ScaleUp SimonsRLERow by factor 3	l8x6	z8k8z6z6t6
Process simons-Arc-Rle-row and apply scaleup by factor 4	k9b6o1b8c4t3f3n7v8	z9t9k6z1z1i1k8o4z3z3z3z3c3z7z7e7z8z8z8j8
simons-Arc-Rle-row histogram	v2j6y6v4	6:37,2:23,4:23
histogram of simons-Arc-Rle-row	r0w5m0w4	0:33,4:24,5:24
histogram of deserialized Simon-ARC-RLE-Row	z4	4:27
Serialize JSON to SIMONARCRLEROW	[4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8]	z4y8
process SimonsRLERow and return histogram	j3o3w6c7v4	3:27,6:24,4:23,7:4
Histogram of simon-Arc-Rle-row	k4m4b9o7t7p2	7:37,4:26,2:17,9:3
ScaleUp Simon-ARC-RLE-Row by factor 4	s6k8a5x9o0e0	z6z6y6z8t8g5z9z9z9r9z0z0z0f0
Change SimonsRLERow to JSON	c7x1	[7,7,7,7,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1]
With Simons-RLE-Row find the histogram	p0	0:17
change json to Simon-ARC-RLE-Row	[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0]	p0n1a0
histogram of SIMONARCRLEROW	k2b4i8v9k70y1	1:26,9:23,2:12,7:12,8:10,4:3,0:1
compress the Simon-ARC-RLE-Row	z5l9	59
Simon-ARC-RLE-Row histogram	p2x8	8:25,2:17
reverse the SimonsRLERow	a2h0r5o3r8	r8o3r5h0a2
convert Simon-ARC-RLE-Row to Digits	r9r6f8y1l0q1	999999999999999999966666666666666666668888888111111111111111111111111110000000000000111111111111111111
convert Digits to SIMONARCRLEROW	9999999999999999999	r9
reverse the simons-Arc-Rle-row	y6	y6
Simon-ARC-RLE-Row compute histogram	y2r6a6u7c6o2c0y3	2:42,3:26,6:25,7:22,0:4
Histogram of Simons-RLE-Row	k8n9r0t2	2:21,0:19,9:15,8:12
remove repeated pixels from Simon-ARC-RLE-Row	i2m2	2
Histogram of simon-Arc-Rle-row	g8p6	6:17,8:8
convert String to SimonsRLERow	888888886666666666666666677777755555555555577779999999999777777777777771111111111111	g8p6e7k5c7i9m7l1
Histogram of simons-Arc-Rle-row	z3	3:27
convert Simon-ARC-RLE-Row and return the histogram	g4g1a7w9w7	7:26,9:24,1:8,4:8
ScaleUp Simon-ARC-RLE-Row by factor 3	f8q6	t8z6z6
With SimonsRLERow populate a histogram	c3v3v5h18o3e8	3:43,5:23,1:9,8:7
convert simons-Arc-Rle-row and return the histogram	e0i0d2	0:16,2:5
Convert json to SimonsRLERow	[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,8,8,8,8,8,8,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3]	o0d2j3e8s2k3
convert SIMONARCRLEROW and return the histogram	y6	6:26
simons-Arc-Rle-row compute histogram	w2w2	2:48
Scale up the Simons-RLE-Row by 3	h8h1t6	z8z1z6z6h6
Convert Simon-ARC-RLE-Row and return histogram	d1c7t8o5w8	8:45,5:16,1:5,7:4
remove repeated pixels from simons-Arc-Rle-row	s7g1d7	717
Serialize Json to SimonsRLERow	[7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7]	s7
Histogram of Simons-RLE-Row	a4m4d2l3j3c5n5u2	2:27,3:24,5:19,4:16
Convert Simon-ARC-RLE-Row and return histogram	e2e1w7w0	0:24,7:24,1:6,2:6
Histogram of SimonsRLERow	y4	4:26
Flipx Simon-ARC-RLE-Row	t4k6d3l3y1	y1q3k6t4
Convert SimonsRLERow and return histogram	x3z3f9w0y0	3:52,0:50,9:7
Transform Symbols to Simon-ARC-RLE-Row	33333333333333333333333333333333333333333333333333339999999000000000000000000000000	z3x3f9w0
ScaleUp simon-Arc-Rle-row by factor 4	q0v7	z0z0q0z7z7z7j7
histogram of deserialized SimonsRLERow	f7g5t4	4:21,5:8,7:7
Process SIMONARCRLEROW and apply scale-up by factor 4	v3	z3z3z3j3

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Version 1

Have dataset items that are somewhat evenly of each type. The LLM learned some of the types fine. However histograms are causing problems.

Version 2

Here the majority of dataset items are histograms. Since this is what my LLM is struggling with.

Downloads last month: 2

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Size of downloaded dataset files:

12 MB

Size of the auto-converted Parquet files:

3.36 MB

Number of rows:

100,000