Data Normalization

Data processing and normalization tasks evaluate structured output from messy prose and different structures. This capability is essential for catalogue and product pipelines where data needs to be extracted from unstructured text and formatted consistently. Models must understand the desired output format and extract relevant information accurately.

28
mistral/mistral-tiny-eu
Average duration
7s
Average tokens
1410
Average cost
$0.00
50
4s
1046
opper_normalization_sample_01
0
3s
1231
opper_normalization_sample_02
0
4s
1350
opper_normalization_sample_03
0
4s
1021
opper_normalization_sample_04
50
4s
1394
opper_normalization_sample_05
50
6s
1378
opper_normalization_sample_06
0
8s
2884
opper_normalization_sample_07
0
4s
1121
opper_normalization_sample_08
50
16s
4211
opper_normalization_sample_09
50
4s
543
opper_normalization_sample_10
0
4s
477
opper_normalization_sample_11
100
3s
699
opper_normalization_sample_12
0
4s
877
opper_normalization_sample_13
100
3s
920
opper_normalization_sample_14
0
5s
1162
opper_normalization_sample_15
50
6s
677
opper_normalization_sample_16
0
4s
672
opper_normalization_sample_17
0
21s
3693
opper_normalization_sample_18
50
34s
2702
opper_normalization_sample_19
50
10s
2344
opper_normalization_sample_20
50
4s
616
opper_normalization_sample_21
0
4s
766
opper_normalization_sample_22
50
6s
1187
opper_normalization_sample_23
0
9s
1610
opper_normalization_sample_24
0
4s
1083
opper_normalization_sample_25
50
4s
1135
opper_normalization_sample_26
0
4s
1260
opper_normalization_sample_27