datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
instruction_filtering_embedding_filter_seed_data_code_w_openthoughtsinstruction_filtering_embedding_filter_mean_seed_data_code_w_openthoughtsb2_code_embeddingembedding_codeb2_code_embedding_10kinstruction_filtering_scale_up_code_base_embedding_filter_mean_per_domain_16Kinstruction_filtering_scale_up_code_base_embedding_filter_meanb2_code_embedding_filter_open_code_reasoninginstruction_filtering_embedding_filter_codeinstruction_filtering_scale_up_code_base_embedding_filter_mean_16Kinstruction_filtering_scale_up_code_base_embedding_filter_mean_per_domaininstruction_filtering_embedding_filter_code_meaninstruction_filtering_scale_up_code_base_embedding_filter_mean_per_domain_8Kb2_code_embedding_3kb2_code_embedding_10k_eval_636d
mlfoundations-dev/b2_code_embedding_10k_eval_636d
Precomputed model outputs for evaluation.
Evaluation Results
Summary
Metric
AIME24
AMC23
MATH500
MMLUPro
JEEBench
GPQADiamond
LiveCodeBench
CodeElo
CodeForces
Accuracy
19.3
50.5
71.0
29.6
27.8
28.3
35.9
8.4
9.0
AIME24
Average Accuracy: 19.33% ± 1.23%
Number of Runs: 10
Run
Accuracy
Questions Solved
Total Questions
1
20.00%
6
30
2
13.33%
4
30
3
20.00%
6
30
4
13.33%
4… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations-dev/b2_code_embedding_10k_eval_636d.b2_code_embedding_0.3k_eval_636d
mlfoundations-dev/b2_code_embedding_0.3k_eval_636d
Precomputed model outputs for evaluation.
Evaluation Results
Summary
Metric
AIME24
AMC23
MATH500
MMLUPro
JEEBench
GPQADiamond
LiveCodeBench
CodeElo
CodeForces
Accuracy
18.7
55.8
74.8
26.6
42.1
34.8
28.2
7.3
8.7
AIME24
Average Accuracy: 18.67% ± 1.84%
Number of Runs: 10
Run
Accuracy
Questions Solved
Total Questions
1
13.33%
4
30
2
13.33%
4
30
3
16.67%
5
30
4
20.00%
6… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations-dev/b2_code_embedding_0.3k_eval_636d.instruction_filtering_scale_up_code_base_embedding_filter_mean_per_domain_4Kb2_code_embedding_1k_eval_636d
mlfoundations-dev/b2_code_embedding_1k_eval_636d
Precomputed model outputs for evaluation.
Evaluation Results
Summary
Metric
AIME24
AMC23
MATH500
MMLUPro
JEEBench
GPQADiamond
LiveCodeBench
CodeElo
CodeForces
Accuracy
12.3
39.2
67.8
26.8
33.9
31.8
19.0
4.3
5.8
AIME24
Average Accuracy: 12.33% ± 2.16%
Number of Runs: 10
Run
Accuracy
Questions Solved
Total Questions
1
10.00%
3
30
2
3.33%
1
30
3
16.67%
5
30
4
6.67%
2
30… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations-dev/b2_code_embedding_1k_eval_636d.b2_code_embedding_3k_eval_636d
mlfoundations-dev/b2_code_embedding_3k_eval_636d
Precomputed model outputs for evaluation.
Evaluation Results
Summary
Metric
AIME24
AMC23
MATH500
MMLUPro
JEEBench
GPQADiamond
LiveCodeBench
CodeElo
CodeForces
Accuracy
21.7
62.5
75.2
28.8
43.8
40.4
34.7
9.4
12.5
AIME24
Average Accuracy: 21.67% ± 1.84%
Number of Runs: 10
Run
Accuracy
Questions Solved
Total Questions
1
16.67%
5
30
2
33.33%
10
30
3
16.67%
5
30
4
20.00%
6… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations-dev/b2_code_embedding_3k_eval_636d.b2_code_embedding_filter_code_golfb2_code_embedding_1kinstruction_filtering_scale_up_code_base_embedding_filter_mean_8Kinstruction_filtering_scale_up_code_base_embedding_filter_mean_per_domain_1Kinstruction_filtering_scale_up_code_base_embedding_filter_mean_per_domain_2Kb2_calc_positive_embeddings_codeb2_calc_positive_embeddings_code_ioib2_code_embedding_0.3kinstruction_filtering_scale_up_code_base_embedding_filter_mean_4Kinstruction_filtering_scale_up_code_base_embedding_filter_mean_2Kinstruction_filtering_scale_up_code_base_embedding_filter_mean_1K