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mHossain/final_train_v4_test_640000
2023-08-19T03:28:37.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 6648643.8 num_examples: 18000 - name: test num_bytes: 738738.2 num_examples: 2000 download_size: 3190543 dataset_size: 7387382.0 --- # Dataset Card for "final_train_v4_test_640000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_660000
2023-08-19T03:28:41.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 6717820.5 num_examples: 18000 - name: test num_bytes: 746424.5 num_examples: 2000 download_size: 3226337 dataset_size: 7464245.0 --- # Dataset Card for "final_train_v4_test_660000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_680000
2023-08-19T03:28:45.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 6705421.2 num_examples: 18000 - name: test num_bytes: 745046.8 num_examples: 2000 download_size: 3198100 dataset_size: 7450468.0 --- # Dataset Card for "final_train_v4_test_680000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_700000
2023-08-19T03:28:51.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 6742140.3 num_examples: 18000 - name: test num_bytes: 749126.7 num_examples: 2000 download_size: 3216875 dataset_size: 7491267.0 --- # Dataset Card for "final_train_v4_test_700000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_720000
2023-08-19T03:28:55.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 6734938.5 num_examples: 18000 - name: test num_bytes: 748326.5 num_examples: 2000 download_size: 3226399 dataset_size: 7483265.0 --- # Dataset Card for "final_train_v4_test_720000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_740000
2023-08-19T03:28:59.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 6717019.5 num_examples: 18000 - name: test num_bytes: 746335.5 num_examples: 2000 download_size: 3224246 dataset_size: 7463355.0 --- # Dataset Card for "final_train_v4_test_740000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_760000
2023-08-19T03:29:03.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 6734172.6 num_examples: 18000 - name: test num_bytes: 748241.4 num_examples: 2000 download_size: 3236773 dataset_size: 7482414.0 --- # Dataset Card for "final_train_v4_test_760000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_780000
2023-08-19T03:29:08.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 6683220.9 num_examples: 18000 - name: test num_bytes: 742580.1 num_examples: 2000 download_size: 3207945 dataset_size: 7425801.0 --- # Dataset Card for "final_train_v4_test_780000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_800000
2023-08-19T03:29:13.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 6685194.6 num_examples: 18000 - name: test num_bytes: 742799.4 num_examples: 2000 download_size: 3208395 dataset_size: 7427994.0 --- # Dataset Card for "final_train_v4_test_800000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_820000
2023-08-19T03:29:17.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 6750900.9 num_examples: 18000 - name: test num_bytes: 750100.1 num_examples: 2000 download_size: 3232883 dataset_size: 7501001.0 --- # Dataset Card for "final_train_v4_test_820000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_840000
2023-08-19T03:29:22.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 7182613.8 num_examples: 18000 - name: test num_bytes: 798068.2 num_examples: 2000 download_size: 3446799 dataset_size: 7980682.0 --- # Dataset Card for "final_train_v4_test_840000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_860000
2023-08-19T03:29:27.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 7271267.4 num_examples: 18000 - name: test num_bytes: 807918.6 num_examples: 2000 download_size: 3497291 dataset_size: 8079186.0 --- # Dataset Card for "final_train_v4_test_860000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_880000
2023-08-19T03:29:31.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 7307297.1 num_examples: 18000 - name: test num_bytes: 811921.9 num_examples: 2000 download_size: 3499994 dataset_size: 8119219.0 --- # Dataset Card for "final_train_v4_test_880000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_900000
2023-08-19T03:29:35.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 7400834.1 num_examples: 18000 - name: test num_bytes: 822314.9 num_examples: 2000 download_size: 3538671 dataset_size: 8223149.0 --- # Dataset Card for "final_train_v4_test_900000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_920000
2023-08-19T03:29:40.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 7524029.7 num_examples: 18000 - name: test num_bytes: 836003.3 num_examples: 2000 download_size: 3597294 dataset_size: 8360033.0 --- # Dataset Card for "final_train_v4_test_920000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_940000
2023-08-19T03:29:44.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 7533398.7 num_examples: 18000 - name: test num_bytes: 837044.3 num_examples: 2000 download_size: 3605948 dataset_size: 8370443.0 --- # Dataset Card for "final_train_v4_test_940000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_960000
2023-08-19T03:29:49.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 7439547.6 num_examples: 18000 - name: test num_bytes: 826616.4 num_examples: 2000 download_size: 3558375 dataset_size: 8266164.0 --- # Dataset Card for "final_train_v4_test_960000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_980000
2023-08-19T03:29:54.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 7397010.9 num_examples: 18000 - name: test num_bytes: 821890.1 num_examples: 2000 download_size: 3537723 dataset_size: 8218901.0 --- # Dataset Card for "final_train_v4_test_980000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_1000000
2023-08-19T03:29:59.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 7463866.5 num_examples: 18000 - name: test num_bytes: 829318.5 num_examples: 2000 download_size: 3566518 dataset_size: 8293185.0 --- # Dataset Card for "final_train_v4_test_1000000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_1020000
2023-08-19T03:30:04.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 7446663.0 num_examples: 18000 - name: test num_bytes: 827407.0 num_examples: 2000 download_size: 3554301 dataset_size: 8274070.0 --- # Dataset Card for "final_train_v4_test_1020000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_1040000
2023-08-19T03:30:09.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 7345201.5 num_examples: 18000 - name: test num_bytes: 816133.5 num_examples: 2000 download_size: 3516028 dataset_size: 8161335.0 --- # Dataset Card for "final_train_v4_test_1040000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
KCode/file-type
2023-08-19T03:45:38.000Z
[ "region:us" ]
KCode
null
null
null
0
0
Entry not found
mHossain/final_train_v4_test_1060000
2023-08-19T03:30:14.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 7384662.0 num_examples: 18000 - name: test num_bytes: 820518.0 num_examples: 2000 download_size: 3543931 dataset_size: 8205180.0 --- # Dataset Card for "final_train_v4_test_1060000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_1080000
2023-08-19T03:30:18.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 7366470.3 num_examples: 18000 - name: test num_bytes: 818496.7 num_examples: 2000 download_size: 3526599 dataset_size: 8184967.0 --- # Dataset Card for "final_train_v4_test_1080000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_1100000
2023-08-19T03:30:23.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 7290159.3 num_examples: 18000 - name: test num_bytes: 810017.7 num_examples: 2000 download_size: 3489433 dataset_size: 8100177.0 --- # Dataset Card for "final_train_v4_test_1100000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_1120000
2023-08-19T03:30:27.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 7308363.6 num_examples: 18000 - name: test num_bytes: 812040.4 num_examples: 2000 download_size: 3492386 dataset_size: 8120404.0 --- # Dataset Card for "final_train_v4_test_1120000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_1140000
2023-08-19T03:30:32.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 7315927.2 num_examples: 18000 - name: test num_bytes: 812880.8 num_examples: 2000 download_size: 3505075 dataset_size: 8128808.0 --- # Dataset Card for "final_train_v4_test_1140000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mHossain/final_train_v4_test_1160000
2023-08-19T03:32:56.000Z
[ "region:us" ]
mHossain
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: string - name: prefix dtype: string splits: - name: train num_bytes: 7153427.7 num_examples: 18000 - name: test num_bytes: 794825.3 num_examples: 2000 download_size: 3422745 dataset_size: 7948253.0 --- # Dataset Card for "final_train_v4_test_1160000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
shockroborty/oasst_best_k2_en
2023-08-20T14:09:15.000Z
[ "region:us" ]
shockroborty
null
null
null
0
0
### Dataset Card This dataset is a subset of the Open Assistant dataset, which you can find here: https://huggingface.co/datasets/OpenAssistant/oasst1/tree/main This subset of the data only contains the highest-rated (quality >= 0.75) english conversation paths of maximum 1 turn - rank 1/top-k=2 - which means the maximum loop one conversation has is Human - Assistant - Human - Assistant, with a total of 4355 samples. If you want all the turns, you can refer to https://huggingface.co/datasets/timdettmers/openassistant-guanaco For further information, please see the original dataset. License: Apache 2.0
alamabdifc/tarkAaM
2023-08-19T04:10:48.000Z
[ "region:us" ]
alamabdifc
null
null
null
0
0
Entry not found
Mariko45654/klokasma3
2023-08-19T04:40:27.000Z
[ "region:us" ]
Mariko45654
null
null
null
0
0
Entry not found
adatngeteh/tOoOng
2023-08-19T04:20:52.000Z
[ "region:us" ]
adatngeteh
null
null
null
0
0
Entry not found
syaifulumar/spartan
2023-08-19T04:29:29.000Z
[ "region:us" ]
syaifulumar
null
null
null
0
0
Entry not found
JorangHorse/Third
2023-08-19T04:35:15.000Z
[ "region:us" ]
JorangHorse
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: audio dtype: audio - name: transcription dtype: string splits: - name: train num_bytes: 1213654.0 num_examples: 2 download_size: 623252 dataset_size: 1213654.0 --- # Dataset Card for "Third" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
IKUTMAIN/WiNnNn
2023-08-19T04:39:15.000Z
[ "region:us" ]
IKUTMAIN
null
null
null
0
0
Entry not found
Neilbert/supytalP-nepO
2023-08-20T04:29:22.000Z
[ "region:us" ]
Neilbert
null
null
null
0
0
Entry not found
danakampanye/cairRr
2023-08-19T04:49:03.000Z
[ "region:us" ]
danakampanye
null
null
null
0
0
Entry not found
gwj/wendi
2023-08-19T05:00:28.000Z
[ "region:us" ]
gwj
null
null
null
0
0
Entry not found
Jing24/generate_sub_0
2023-08-19T05:03:51.000Z
[ "region:us" ]
Jing24
null
null
null
0
0
--- dataset_info: features: - name: id dtype: string - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: answers struct: - name: answer_start sequence: int64 - name: text sequence: string splits: - name: train num_bytes: 71556466 num_examples: 78391 download_size: 12827716 dataset_size: 71556466 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "generate_sub_0" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Mahamed12v/Kenya87r
2023-08-19T05:24:40.000Z
[ "license:openrail", "region:us" ]
Mahamed12v
null
null
null
0
0
--- license: openrail ---
tyuykiulpolui/yjyukiopoujty546
2023-08-19T05:26:02.000Z
[ "region:us" ]
tyuykiulpolui
null
null
null
0
0
Entry not found
ytukyilupu/jyukyiuopk6676
2023-08-19T05:26:08.000Z
[ "region:us" ]
ytukyilupu
null
null
null
0
0
Entry not found
yjuykiuop/htyjuykiuok76
2023-08-19T05:26:23.000Z
[ "region:us" ]
yjuykiuop
null
null
null
0
0
Entry not found
Mustain/squad
2023-08-19T05:32:45.000Z
[ "region:us" ]
Mustain
null
null
null
0
0
Entry not found
james0707/sentiment-uz
2023-08-19T05:41:23.000Z
[ "region:us" ]
james0707
null
null
null
0
0
Entry not found
AttainBase/AttainDataset
2023-08-19T06:15:30.000Z
[ "license:openrail", "region:us" ]
AttainBase
null
null
null
0
0
--- license: openrail ---
SUSTech/sci-llm
2023-08-19T06:43:31.000Z
[ "license:apache-2.0", "region:us" ]
SUSTech
null
null
null
0
0
--- license: apache-2.0 dataset_info: features: - name: chosen dtype: string - name: rejected dtype: string splits: - name: train num_bytes: 47624714 num_examples: 133542 - name: test num_bytes: 422106 num_examples: 800 download_size: 89497 dataset_size: 48046820 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
oklinkrimfc/jilat
2023-08-19T06:39:21.000Z
[ "region:us" ]
oklinkrimfc
null
null
null
0
0
Entry not found
Jing24/generate_sub_1
2023-08-19T06:39:49.000Z
[ "region:us" ]
Jing24
null
null
null
0
0
--- dataset_info: features: - name: id dtype: string - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: answers struct: - name: answer_start sequence: int64 - name: text sequence: string splits: - name: train num_bytes: 63954468 num_examples: 70370 download_size: 11445492 dataset_size: 63954468 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "generate_sub_1" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Michael823/semantic-try2
2023-08-19T06:45:21.000Z
[ "region:us" ]
Michael823
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: pixel_values dtype: image - name: label dtype: image splits: - name: train num_bytes: 3347017.0 num_examples: 10 - name: validation num_bytes: 834103.0 num_examples: 3 download_size: 4200704 dataset_size: 4181120.0 --- # Dataset Card for "semantic-try2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
antonjaragon/audio-emotions
2023-08-19T17:19:15.000Z
[ "region:us" ]
antonjaragon
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: paths dtype: string - name: labels dtype: string splits: - name: train num_bytes: 624270.4512534819 num_examples: 9764 - name: test num_bytes: 156131.5487465181 num_examples: 2442 download_size: 167160 dataset_size: 780402.0 --- # Dataset Card for "audio-emotions" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Ebo88/llama2-3
2023-08-19T07:27:20.000Z
[ "license:apache-2.0", "region:us" ]
Ebo88
null
null
null
0
0
--- license: apache-2.0 ---
Akshithsak/demo
2023-08-19T07:16:01.000Z
[ "region:us" ]
Akshithsak
null
null
null
0
0
Entry not found
chargoddard/Open-Platypus-Chat-Judged
2023-08-19T08:20:10.000Z
[ "size_categories:10K<n<100K", "region:us" ]
chargoddard
null
null
null
0
0
--- dataset_info: - config_name: best_rated features: - name: id dtype: string - name: rating struct: - name: analysis dtype: string - name: judge dtype: string - name: score dtype: int64 - name: conversations list: - name: from dtype: string - name: value dtype: string splits: - name: train num_bytes: 16455644.962765958 num_examples: 10236 download_size: 7071171 dataset_size: 16455644.962765958 - config_name: default features: - name: id dtype: string - name: rating struct: - name: analysis dtype: string - name: judge dtype: string - name: score dtype: int64 - name: conversations list: - name: from dtype: string - name: value dtype: string splits: - name: train num_bytes: 39894811 num_examples: 24816 download_size: 18554361 dataset_size: 39894811 - config_name: worst_rated features: - name: id dtype: string - name: rating struct: - name: analysis dtype: string - name: judge dtype: string - name: score dtype: int64 - name: conversations list: - name: from dtype: string - name: value dtype: string splits: - name: train num_bytes: 236320.80984042553 num_examples: 147 download_size: 125546 dataset_size: 236320.80984042553 configs: - config_name: best_rated data_files: - split: train path: best_rated/train-* - config_name: default data_files: - split: train path: data/train-* - config_name: worst_rated data_files: - split: train path: worst_rated/train-* size_categories: - 10K<n<100K --- # Dataset Card for "Open-Platypus-Chat-Judged" This is [Open-Platypus-Chat](https://huggingface.co/datasets/chargoddard/Open-Platypus-Chat), judged for quality by [TheBloke/OpenOrca-Platypus2-13B-GPTQ](https://huggingface.co/TheBloke/OpenOrca-Platypus2-13B-GPTQ). Each row is annotated with a score on a scale of 1 to 5 and a brief explanation of why it was given that score. As the "judge" was a relatively quite small model, and quantized at that, the ratings are far from perfect. This is from the first iteration of an experiment in dataset refinement. Definitely do not take this dataset as ground truth. <sub>Or do. I'm a dataset card, not a cop.</sub>
PiyushVerma/Flipkart30k
2023-08-19T07:21:44.000Z
[ "region:us" ]
PiyushVerma
null
null
null
0
0
Entry not found
celiksa/train_dataset
2023-08-19T08:14:42.000Z
[ "region:us" ]
celiksa
null
null
null
0
0
Entry not found
mesolitica/kamus-dewan
2023-08-19T08:24:00.000Z
[ "region:us" ]
mesolitica
null
null
null
0
0
Entry not found
jxie/shapenet55
2023-08-19T08:39:24.000Z
[ "region:us" ]
jxie
null
null
null
0
0
--- dataset_info: features: - name: inputs sequence: sequence: float64 - name: labels dtype: int64 splits: - name: train num_bytes: 12035988360 num_examples: 52470 download_size: 9149702428 dataset_size: 12035988360 --- # Dataset Card for "shapenet55" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
deeplearning-tide/actresses
2023-08-19T09:04:16.000Z
[ "region:us" ]
deeplearning-tide
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: val path: data/val-* - split: test path: data/test-* dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': keira '1': nathalie '2': others splits: - name: train num_bytes: 137979476.0 num_examples: 429 - name: val num_bytes: 54519033.0 num_examples: 168 - name: test num_bytes: 54024602.0 num_examples: 168 download_size: 246545069 dataset_size: 246523111.0 --- # Dataset Card for "actresses" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Jing24/generate_sub_2
2023-08-19T08:36:50.000Z
[ "region:us" ]
Jing24
null
null
null
0
0
--- dataset_info: features: - name: id dtype: string - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: answers struct: - name: answer_start sequence: int64 - name: text sequence: string splits: - name: train num_bytes: 57007597 num_examples: 62522 download_size: 10151425 dataset_size: 57007597 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "generate_sub_2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
iliang/NeuralActivityDemo
2023-08-19T09:41:50.000Z
[ "region:us" ]
iliang
null
null
null
0
0
# Demo Data for "Global spatiotemporal structure and its deviations of neural activities in mice: a resting-state waves perspective" ## Dependencies * Python. * Python packages in "requirements.txt". ## How to run it * Install Python. * Install all required Python packages using something like ```pip install -r requirements.txt```. * You can just run ```python demo.py``` to get a demo result. Or if you prefer jupyter, simply open ```demo.ipynb```. Please refer to ```demo.ipynb``` for instructions on how to execute the code on your data and to view the expected outputs. Please note that lines 24 to 26 in ```demo.py``` may take a few minutes to execute, so please be patient. ## Tested on * Arch Linux (6.4.10-arch1-1). * Python 3.11.3. * At least 128G memory if you want compute FC of all pixel pairs (using ```rsfc.full_image_pipeline``` function).
nc33/triplet_sbert_law2
2023-08-20T15:05:30.000Z
[ "region:us" ]
nc33
null
null
null
0
0
--- dataset_info: config_name: train features: - name: question dtype: string - name: positive dtype: string - name: negative dtype: string - name: id dtype: string splits: - name: train num_bytes: 1133470947 num_examples: 335510 download_size: 93896594 dataset_size: 1133470947 configs: - config_name: train data_files: - split: train path: train/train-* --- # Dataset Card for "triplet_sbert_law2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
reprography/output
2023-08-19T08:57:23.000Z
[ "license:openrail++", "region:us" ]
reprography
null
null
null
0
0
--- license: openrail++ ---
cockamamie/powered
2023-08-19T09:01:14.000Z
[ "license:bsl-1.0", "region:us" ]
cockamamie
null
null
null
0
0
--- license: bsl-1.0 ---
grattoir/quicker
2023-08-19T09:04:39.000Z
[ "region:us" ]
grattoir
null
null
null
0
0
Entry not found
hijinks/smarter
2023-08-19T09:10:00.000Z
[ "license:bsd-3-clause-clear", "region:us" ]
hijinks
null
null
null
0
0
--- license: bsd-3-clause-clear ---
fengtc/users_manual
2023-08-19T13:20:41.000Z
[ "license:apache-2.0", "region:us" ]
fengtc
null
null
null
0
0
--- license: apache-2.0 ---
tarsomcareen/storage
2023-08-19T09:14:24.000Z
[ "license:cc-by-2.0", "region:us" ]
tarsomcareen
null
null
null
0
0
--- license: cc-by-2.0 ---
bogeyturn/Hitomila-metadata-dump
2023-08-28T17:57:01.000Z
[ "size_categories:1M<n<10M", "language:en", "language:ja", "not-for-all-audiences", "region:us" ]
bogeyturn
null
null
null
0
0
--- language: - en - ja tags: - not-for-all-audiences size_categories: - 1M<n<10M ---
taesiri/FragileX
2023-08-20T01:12:30.000Z
[ "license:mit", "region:us" ]
taesiri
null
null
null
0
0
--- license: mit ---
stampylongmoue/business
2023-08-19T09:18:19.000Z
[ "license:cc-by-nc-nd-4.0", "region:us" ]
stampylongmoue
null
null
null
0
0
--- license: cc-by-nc-nd-4.0 ---
jzdesign/mid-test
2023-08-19T09:32:37.000Z
[ "license:openrail", "region:us" ]
jzdesign
null
null
null
0
0
--- license: openrail ---
DebajyotyBanik/ML-based-MT-Datasets
2023-08-19T09:39:13.000Z
[ "region:us" ]
DebajyotyBanik
null
null
null
0
0
Entry not found
amrllama/sample
2023-08-19T10:27:18.000Z
[ "region:us" ]
amrllama
null
null
null
0
0
Entry not found
sungmogi/en2ko_hiphop
2023-08-27T08:28:05.000Z
[ "task_categories:translation", "size_categories:10K<n<100K", "language:en", "language:ko", "region:us" ]
sungmogi
null
null
null
1
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: valid path: data/valid-* dataset_info: features: - name: id dtype: int64 - name: translation struct: - name: en dtype: string - name: ko dtype: string splits: - name: train num_bytes: 5061272.804687347 num_examples: 46158 - name: test num_bytes: 281254.92317741335 num_examples: 2565 - name: valid num_bytes: 281145.272135239 num_examples: 2564 download_size: 4172120 dataset_size: 5623673 task_categories: - translation language: - en - ko pretty_name: en2ko_hiphop size_categories: - 10K<n<100K --- # Dataset Card for "en2ko_hiphop" ## Copyright Disclaimer The dataset "en2ko_hiphop" was curated from publicly available sources and is believed to be in the public domain. The translations provided in this dataset are the work of volunteers and members of the community, and they have been collected and curated to facilitate research and analysis. However, it is important to acknowledge that copyright issues cannot be entirely ruled out. Therefore, users of the dataset should exercise caution when using it. The author of en2ko_hiphop does not assume any legal responsibility for the use of the dataset. If you have any questions or concerns regarding the dataset's copyright status, please contact the author at sungcho2023@u.northwestern.edu. ## Acknowledgements I gratefully acknowledge DanceD(http://danced.co.kr/) of Korean Hiphop community HIPHOPLE(https://hiphople.com/). All English-to-Korean translations have been provided by DanceD.
Jing24/generate_sub_3
2023-08-19T10:54:57.000Z
[ "region:us" ]
Jing24
null
null
null
0
0
--- dataset_info: features: - name: id dtype: string - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: answers struct: - name: answer_start sequence: int64 - name: text sequence: string splits: - name: train num_bytes: 50105322 num_examples: 54802 download_size: 8946878 dataset_size: 50105322 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "generate_sub_3" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
tyang816/MedChatZH
2023-08-22T02:37:57.000Z
[ "task_categories:question-answering", "size_categories:100K<n<1M", "language:zh", "license:apache-2.0", "medical", "biology", "region:us" ]
tyang816
null
null
null
0
0
--- license: apache-2.0 task_categories: - question-answering language: - zh tags: - medical - biology size_categories: - 100K<n<1M ---
Imama/ClothoAQA
2023-08-19T11:34:51.000Z
[ "task_categories:question-answering", "size_categories:100K<n<1M", "language:en", "region:us" ]
Imama
null
null
null
0
0
--- task_categories: - question-answering language: - en pretty_name: Clotho-AQA size_categories: - 100K<n<1M ---
PhucDucAnh/Opensun3dtestset
2023-08-19T13:06:45.000Z
[ "region:us" ]
PhucDucAnh
null
null
null
0
0
Entry not found
YangYan/Instruction
2023-09-11T17:29:16.000Z
[ "region:us" ]
YangYan
null
null
null
0
0
Entry not found
Eim/laravel-docs
2023-08-19T12:10:32.000Z
[ "region:us" ]
Eim
null
null
null
1
0
Entry not found
AK-12/Medical_Data
2023-08-19T12:19:49.000Z
[ "task_categories:question-answering", "language:en", "region:us" ]
AK-12
null
null
null
0
0
--- task_categories: - question-answering language: - en ---
anujsahani01/Unclean_Data
2023-08-19T12:38:49.000Z
[ "region:us" ]
anujsahani01
null
null
null
0
0
Entry not found
billionairebrainwave/Billionaire-Brain-Wave
2023-08-19T12:33:24.000Z
[ "region:us" ]
billionairebrainwave
null
null
null
0
0
<h3 class="articleHeading mb-0" style="text-align: left;"><span style="color: red;">Billionaire Brain Wave</span><br />Sale Is Live Order Now - <a href="https://sale365day.com/get-billionnaire-brain">https://sale365day.com/get-billionnaire-brain </a></h3> <p class="articleHeading mb-0">Every person desires to live a life filled with peace and happiness but many people find it hard to lead a joyful life and in most cases, this is because of the financial crisis and difficulties that they are in.</p> <p style="text-align: justify;">Now you must be wondering, how can you activate Theta waves in your brain and suppress the Beta wave, then read the <a href="https://billionaire-brain-wave-program.company.site/">Billionaire Brain Wave</a> reviews to know about a program that might assist you in switching on a path to luck and financial independence.</p> <p style="text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjaFoKqoz3qMno587msL68lyDqUUpMd-0Lqpp_t8QY7KydDu6WEo24JHsknuBsX2NgVA9QTEU8AO16i6hi-oMQkAugIAh0C-UfIe3kkRfdE-PdEupa8w_ecr29CF2yyo4NCoXIVeRXGVq7vL-wE-bVYtvk0lz-35PpwKOV3oeAY4zmgtMyqIeWg8_fPJcI/s986/wqwd.JPG"><img src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjaFoKqoz3qMno587msL68lyDqUUpMd-0Lqpp_t8QY7KydDu6WEo24JHsknuBsX2NgVA9QTEU8AO16i6hi-oMQkAugIAh0C-UfIe3kkRfdE-PdEupa8w_ecr29CF2yyo4NCoXIVeRXGVq7vL-wE-bVYtvk0lz-35PpwKOV3oeAY4zmgtMyqIeWg8_fPJcI/w640-h274/wqwd.JPG" alt="" width="640" height="274" border="0" data-original-height="422" data-original-width="986" /></a> </p> <p style="text-align: justify;"><strong><u><a href="https://sale365day.com/get-billionnaire-brain" target="_blank" rel="nofollow noopener"><span style="font-size: large;">Click Here To Purchase Billionaire Brain Wave Program at official website</span></a></u></strong></p> <h2 style="text-align: justify;"><strong>What Is Billionaire Brain Wave Program?</strong></h2> <p style="text-align: justify;">First things first, let&rsquo;s start with discussing what <a href="https://vocal.media/stories/billionaire-brain-wave-100-trusted-is-it-proven-or-fake-money-booster">Billionaire Brain Wave</a> is. The program, <a href="https://billionaire-brain-wave-official.jimdosite.com/">Billionaire Brain Wave</a>, is created to help people achieve their true and maximum potential by providing them with the audio frequencies needed to activate the Theta brain wave. By doing this, Billionaire Brain Wave is supporting you in attaining all the wealth and happiness that you need in your life. The audio program is created based on ancient studies and scientific research evidence that proves that the real thing that has helped the upper-class elite people stay wealthy even in the toughest of times is the Theta brain wave in their brains</p> <h2 style="text-align: justify;"><strong>Creators of the Billionaire Brain Wave Program</strong></h2> <p style="text-align: justify;"><a href="https://fit-breath.blogspot.com/2023/08/billionaire-brain-wave.html">Billionaire Brain Wave</a>&nbsp;is created by Dave Mitchell and Dr. Summers. Dave Mitchell is a husband and father who has been in a financial situation where he wasn&rsquo;t even able to afford a birthday gift for his daughter. Mitchell met Dr. Summers accidentally from whom he learned about the brain waves that synchronize with wealth and happiness. Dr. Summers is a neuroscientist who along with a team of other scientists developed a 7-minute technology that can aid in activating the brain waves but after the program was developed, they were restricted from sharing about this with the common people. But Dr. Summers, after hearing about the struggles Mitchell is facing in his life, decides to try out the program on him. After listening to the audio frequency, Mitchell became financially successful and happy in the next few months and this led to the creation of <a href="https://www.townscript.com/e/billionaire-brain-wave-program-warning-scam-exposed-does-it-work-014021">Billionaire Brain Wave</a>.</p> <p style="text-align: justify;">Billionaire Brain Wave isn&rsquo;t only a program intended to help people attract wealth and luck to their life but can aid a person in taking the reins of their life and living happily in every hardship situation. <a href="https://www.provenexpert.com/billionaire-brain-wave-program/">Billionaire Brain Wave</a> can help a person in attaining financial freedom, acquire luck in many different ways, become happy, enhance their mental well-being, restore their self-confidence, and lead a joyful life.</p> <p style="text-align: justify;"><strong><u><a href="https://sale365day.com/get-billionnaire-brain" target="_blank" rel="nofollow noopener"><span style="font-size: large;">Click Here To Purchase Billionaire Brain Wave Program at official website</span></a></u></strong> </p> <h2 style="text-align: justify;"><strong>What Are Brain Waves? Understanding Different Brain Waves</strong></h2> <p style="text-align: justify;">So far, we gave you a simple overview of the <a href="https://billionairebrainwaveupdate.contently.com/">Billionaire Brain Wave</a> and talked about the role that waves like beta and theta play in our lives. Now to understand how the program works, it is crucial to understand the five main types of waves produced by the brain and the role each of them plays. Let&rsquo;s take a look at each of these brain waves:</p> <p style="text-align: justify;"><strong>Gamma waves: </strong>Gamma waves are associated with concentration. This is the type of wave that helps a person in attaining maximum focus and gives you the ability to solve any problem quickly. Gamma waves also help with processing information efficiently.</p> <p style="text-align: justify;"><strong>Beta waves: </strong>Beta waves are associated with the daily lives of people. This is the type of wave that comes with being busy and negatively affects your body and brain. <u><a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/beta-wave" target="_blank" rel="nofollow noopener">Beta waves</a></u> are responsible for failures in your life and limiting your potential to a minimum.</p> <p style="text-align: justify;"><strong>Alpha waves: </strong>Alpha waves are waves produced when a person is relaxed and inattentive. These waves are associated with calmness and when the person isn&rsquo;t concentrating or focusing on anything. Alpha waves support peaceful mental well-being.</p> <p style="text-align: justify;"><strong>Theta waves: </strong>Theta waves are the ones associated with wealth and are considered the path to success. Theta waves can help with creativity, productivity, and attaining maximum potential.</p> <p style="text-align: justify;"><strong>Delta waves: </strong>Delta waves are associated with sleep. These waves are produced to help the brain in recovering and stay relaxed, which induces sleep. Delta waves also provide maximum calmness to your brain.</p> <p style="text-align: justify;">These are the 5 major waves produced by the brain. Among these, the ones that are relevant in attaining wealth and happiness in a person&rsquo;s life are theta and beta. Beta is the slave wave of our brain that always succumbs to outside stress and limits a person&rsquo;s potential. Theta is one that a person needs to attract luck and wealth to their lives. Here, the problem is, in the majority of people, beta waves are more dominant than theta waves which lead to a more stressful and unhappy life. So to become financially sound and successful, one should be able to produce more theta waves in the brain. </p> <div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh-s4Khw6yecfIUCg-DgYUR4nQVsa2-OffbZydHSI6__Pll_sPg3qePAeJSmcWbXELljUHCXRO7ElCQZO-PGjua942YBBZcz0JV4_w3oD1hmRmj_Jki5R5aAcYdTQ8-ijDsTJ3S_PYtLtL3GAS-BxmfItd-Tcr-JZnKtAepUPhMF9YJUAwHbJcwPG5ORFI/s671/wfwddwd.JPG"><img src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh-s4Khw6yecfIUCg-DgYUR4nQVsa2-OffbZydHSI6__Pll_sPg3qePAeJSmcWbXELljUHCXRO7ElCQZO-PGjua942YBBZcz0JV4_w3oD1hmRmj_Jki5R5aAcYdTQ8-ijDsTJ3S_PYtLtL3GAS-BxmfItd-Tcr-JZnKtAepUPhMF9YJUAwHbJcwPG5ORFI/w640-h434/wfwddwd.JPG" alt="" width="640" height="434" border="0" data-original-height="456" data-original-width="671" /></a> </div> <p style="text-align: justify;"><strong><u><a href="https://sale365day.com/get-billionnaire-brain" target="_blank" rel="nofollow noopener"><span style="font-size: large;">Click Here To Purchase Billionaire Brain Wave Program at official website</span></a></u></strong></p> <h2 style="text-align: justify;"><strong>The Science Behind Billionaire Brain Wave</strong></h2> <p style="text-align: justify;">We have talked about the&nbsp;<a href="https://billionairebrainwaveupdate.bandcamp.com/track/billionaire-brain-wave-fraud-alert-2023-is-it-really-attracts-money-or-fake-claim">Billionaire Brain Wave program</a> and different types of brain waves in detail. Now let&rsquo;s see the science behind the program and the role that it plays in activating your <u><a href="https://www.healthline.com/health/theta-waves" target="_blank" rel="nofollow noopener">theta brain waves</a></u>. Many scientific studies have found that the source of theta brain waves is a tiny walnut-sized region in the brain and is called the hippocampus. So, if you have a bigger hippocampus, you will have a larger number of theta waves in your brain.</p> <p style="text-align: justify;">But the problem here is that many people have a small-sized hippocampus region which makes it difficult for them to activate the theta waves in their brains. This is one of the primary reasons why a person is not able to reach their full potential and attract all the wealth and happiness in their lives. The condition where your hippocampus is small is called the Shrunken Hippocampus Effect. This happens when the slave waves aka the beta waves attack your brain waves and block the activation of the theta brain. Therefore, to produce more theta waves in your brain, the first thing that needs to be worked on is the Shrunken Hippocampus Effect.</p> <p style="text-align: justify;">A research study from Kyoto University showed that sound waves can make changes in the way that a brain functions. Many other ancient studies have also shown that sound waves play a very major role in activating brain waves. So, to activate the theta brain waves in your brain, the creator of <a href="https://billionairebrainwave.godaddysites.com/">Billionaire Brain Wave</a> created a sound frequency that targets the hippocampus in your brain that puts your brain immediately into a neuroplastic state where more theta waves are produced 6x times faster than other brain waves. The sound waves produced by the creator of the program have 9 decimal points and hit 3 frequencies simultaneously that activate the theta waves in your brain and attract wealth without any difficulties.</p> <p style="text-align: justify;"><strong><u><a href="https://sale365day.com/get-billionnaire-brain" target="_blank" rel="nofollow noopener"><span style="font-size: large;">Click Here To Purchase Billionaire Brain Wave Program at official website</span></a></u></strong> </p> <h2 style="text-align: justify;"><strong>Billionaire Brain Wave Program Benefits and Results</strong></h2> <p style="text-align: justify;">The <a href="https://soundcloud.com/billionaire-brain-wave/billionaire-brain-wave-scientifically-proven-that-attracts-money-effortlessly">Billionaire Brain Wave</a> program can aid in activating theta waves in the brain and offer all the benefits associated with the wave. Some of the benefits that one can expect from listening to the audio track included in the program include the following:</p> <p style="text-align: justify;"><strong>Attracts wealth: </strong>The primary benefit that one can expect from using <a href="https://www.fuzia.com/article_detail/799343/billionaire-brain-wave-2023-dont-buy-till-you-read-thi">Billionaire Brain Wave</a> is that they will be able to attract wealth in their lives. This will help them to become financially independent and live a lavish and luxurious life that they have always desired. By activating the theta waves in your brain, Billionaire Brain Wave is also ensuring that your ability to attract money stays in your life permanently, and it also passes down to the next generation.</p> <p style="text-align: justify;"><strong>Improved focus, productivity, and learning capabilities: </strong>Another benefit that you can get by listening to the Billionaire Brain Wave is improved focus, productivity, and learning capabilities. Along with activating the theta waves in your brain, the audio track of the program also restricts the beta waves from other waves in the brain. This will support its normal production, which thus aids in improving focus and learning capabilities.</p> <p style="text-align: justify;"><strong>Enhanced creativity and problem-solving skills:&nbsp;</strong><a href="https://www.forexagone.com/forum/experiences-trading/billionaire-brain-wave-update-warning-know-the-truth-behind-this-before-buying-58200#155335">Billionaire Brain Wave</a> can also aid in improving your creativity and helping you understand your ambitions more. By listening to the audio, you will be able to think more creatively and develop the ambition that you have fruitfully. Activating the theta waves in your brain with the help of Billionaire Brain Wave also improves problem-solving skills.</p> <p style="text-align: justify;"><strong>Reduced stress and anxiety:&nbsp;</strong><a href="https://groups.google.com/g/billionaire-brain-wave-update/c/b9WfzqtTYvQ">Billionaire Brain Wave</a> can also reduce stress and anxiety. The program does this by calming your brain and putting everything at ease. By activating the theta waves in your brain, Billionaire Brain Wave is relaxing your mind and brain and this can greatly improve your mood. In addition to this, the program is creating a pathway to success which also helps with stress.</p> <p style="text-align: justify;"><strong>Increased motivation and self-confidence:&nbsp;</strong><a href="https://groups.google.com/g/billionaire-brain-wave-update/c/JqttphVTJ7A">Billionaire Brain Wave</a> can also aid in increasing your motivation and self-confidence. The program can help you in feeling better about yourself which will boost your confidence. By unlocking the maximum potential inside you, Billionaire Brain Wave is boosting your motivation.</p> <p style="text-align: justify;">Besides these benefits, a large hippocampus and increased production of theta waves in your brain can also deliver a few other health benefits such as the following:</p> <p style="text-align: justify;">Helps in fighting age-related issues such as dementia</p> <p style="text-align: justify;">Increasing life expectancy</p> <p style="text-align: justify;">Improves brain function in people of all ages</p> <p style="text-align: justify;">Boosting your intelligence </p> <div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjJpDmGhfDSGRhQ_Zh-jIdNQczgCX6ifWD0WbkclRVBOeyDUoSfRaqYrPWuz-3W7VdvACToUsVgfbzeQjkpdnfmh8phzjmwZZVPiIMwFu89_Y7uFTYINZgsWxDHu-kbUHurJyGlCvXlKJf5ckbYfbXB0Ucf48T3BC-tpoxn2pCe3yWP5asW3Px5Sftb6K4/s753/qdeee.JPG"><img src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjJpDmGhfDSGRhQ_Zh-jIdNQczgCX6ifWD0WbkclRVBOeyDUoSfRaqYrPWuz-3W7VdvACToUsVgfbzeQjkpdnfmh8phzjmwZZVPiIMwFu89_Y7uFTYINZgsWxDHu-kbUHurJyGlCvXlKJf5ckbYfbXB0Ucf48T3BC-tpoxn2pCe3yWP5asW3Px5Sftb6K4/w640-h462/qdeee.JPG" alt="" width="640" height="462" border="0" data-original-height="544" data-original-width="753" /></a> </div> <p style="text-align: justify;"><strong><u><a href="https://sale365day.com/get-billionnaire-brain" target="_blank" rel="nofollow noopener"><span style="font-size: large;">Click Here To Purchase Billionaire Brain Wave Program at official website</span></a></u></strong></p> <h2 style="text-align: justify;"><strong>How to Use the Billionaire Brain Wave?</strong></h2> <p style="text-align: justify;">Now, a question you might have in your mind is how to use the <a href="https://groups.google.com/g/billionaire-brain-wave-update">Billionaire Brain Wave</a>. This is quite simple. After waking up in the morning, sit down with your breakfast or the beverage that you like and then listen to the 7-minute audio by putting on your headphones and earbuds. Just listen to the audio tracks continuously and your brain will be able to widen the hippocampus and produce more theta waves.</p> <p style="text-align: justify;">The creator of <a href="https://www.facebook.com/profile.php?id=61550158719435">Billionaire Brain Wave</a> suggests that you listen to the audio track at least one time a day, in the morning. But if you want, you can listen to the audio more than one time a day at a time that you prefer. It is recommended that you listen to the audio in an atmosphere where everything is calm and there are no disturbances or distractions.</p> <h2 style="text-align: justify;"><strong>Billionaire Brain Wave Pricing and Accessibility</strong></h2> <p style="text-align: justify;">The creators of <a href="https://billionaire-brain-wave-2023.webflow.io/">Billionaire Brain Wave</a> have created the program with the intention of helping out people who are struggling in their lives. Therefore, they didn&rsquo;t price the program at a cost that is beyond what a person can afford. The cost of Billionaire Brain Wave is only<strong> $39</strong>. The creator of the program says that this is the price that they had to spend on developing the program. For this <strong>$39</strong>, you will get access to the 7-minute audio incorporated in the Billionaire Brain Wave program. You can now <u><a href="https://sale365day.com/get-billionnaire-brain" target="_blank" rel="nofollow noopener">get Billionaire Brain Wave from the official website</a></u> which is the only place where the program is available.</p> <p style="text-align: justify;">The creator of Billionaire Brain Wave is providing the users of the program with a 90-day refund policy. So if you are not satisfied with the results that the program gave you even after listening to the audio tracks for a few months, then you can get a refund using the money-back guarantee.</p> <p style="text-align: justify;"><strong><u><a href="https://sale365day.com/get-billionnaire-brain" target="_blank" rel="nofollow noopener"><span style="font-size: large;">Click Here To Purchase Billionaire Brain Wave Program at official website</span></a></u></strong></p> <h2 style="text-align: justify;"><strong>Billionaire Brain Wave Bonuses</strong></h2> <p style="text-align: justify;">Along with the <a href="https://infogram.com/billionaire-brain-wave-program-scientifically-proven-by-four-neuroscience-labs-that-attracts-money-effortlessly-1hdw2jpommdqj2l">Billionaire Brain Wave program</a>, the creator is offering four free bonuses to their users. The bonuses are the ones given below:</p> <p style="text-align: justify;"><strong>Bonus 1 - The Warren Buffett Pyramid: How To Invest Your New Fortune Into An Endless Money Supply:</strong> This is the first bonus that you get with Billionaire Brain Wave. The bonus will tell you about 3 simple steps that you can follow to earn more money in your life and improve the effectiveness of Billionaire Brain Wave.</p> <p style="text-align: justify;"><strong>Bonus 2 - 7 Lazy Millionaire Habits: </strong>The second bonus you get with Billionaire Brain Wave is 7 Lazy Millionaire Habits. This bonus contains confessions of some of the lazy and rich people that are making millions of dollars in their lives without any hard work.</p> <p style="text-align: justify;"><strong>Bonus 3 - Quick Cash Manifestation: </strong>The third bonus that comes with <a href="https://colab.research.google.com/drive/1M4sGwm3y0cKd5bDrn5hkBurfT5BrytMy">Billionaire Brain Wave</a> is Quick Cash Manifestation. This is a sound wave that is created with the aim of attracting wealth and money to your life. This bonus is ideal for people who want to manifest a large sum of money in their life.</p> <p style="text-align: justify;"><strong>Bonus 4 - 500 Billionaire Brain Wave Success Stories: </strong>The last bonus that comes with <a href="https://lookerstudio.google.com/reporting/9cb64507-5056-4650-87e5-07704a76c13a/page/f6GaD">Billionaire Brain Wave</a> is 500 Billionaire Brain Wave Success Stories. This bonus contains real stories from 500 customers of the program that will tell you about how they have gained wealth and peacefulness in their lives after using Billionaire Brain Wave.</p> <h2 style="text-align: justify;"><strong>Final words of The Billionaire Brain Wave Reviews</strong></h2> <p style="text-align: justify;">In this Billionaire Brain Wave review, we discussed all of the things related to the program in detail to give you a clear understanding of it. Before we conclude, let&rsquo;s take a quick run of the things that we talked about. Billionaire Brain Wave is a program created to help people in manifesting wealth and happiness in their lives. According to the <a href="https://medium.com/@brainwavenew/billionaire-brain-wave-program-scientifically-proven-by-labs-that-attracts-money-effortlessly-8f01437db9ee">Billionaire Brain Wave Reviews</a>, The program is created by a team of neuroscientists and psychologists based on ancient studies and scientific research. Billionaire Brain Wave consists of a 7-minute sound frequency audio that works on widening the hippocampus in your brain which leads to the development of theta waves in your brain. When there are enough active theta waves in your brain, you will be able to attract more wealth to your life and improve your overall well-being in all aspects.</p> <p style="text-align: justify;">At present, <a href="https://billionaire-brain-wave-update.hashnode.dev/billionaire-brain-wave-program-scientifically-proven-that-attracts-money-effortlessly">Billionaire Brain Wave</a> can be accessed only through the official website of the program by paying $39. The creator of the program is offering a 90-day money-back protection for the users which ensures that spending money on Billionaire Brain Wave is risk-free. In addition, you also get four free bonuses which will make your journey with the program more effective. All in all, <a href="https://devfolio.co/@billionairewave">Billionaire Brain Wave</a> seems to be really helpful for people who want to activate their theta brain waves and attract happiness and wealth to their lives. </p> <div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiA-loHy9l5qFh9utmFAFDVvi8hIAGLxvzYv7ImT9PU-PbjHj2Xwo2dgYkfVNZQeeXTTt-61bWWL64fMDaWAH4aCHr-S7ZTcwFIYmLwsDcmwxP-9t4UyMk1OSrEolA7Nw1OjWnQ8twaekVOKGcJrvgUPoxhlKlts3ooTmG7Utc6nBw-6wXzVgvwyALBrKA/s754/wdfwf.JPG"><img src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiA-loHy9l5qFh9utmFAFDVvi8hIAGLxvzYv7ImT9PU-PbjHj2Xwo2dgYkfVNZQeeXTTt-61bWWL64fMDaWAH4aCHr-S7ZTcwFIYmLwsDcmwxP-9t4UyMk1OSrEolA7Nw1OjWnQ8twaekVOKGcJrvgUPoxhlKlts3ooTmG7Utc6nBw-6wXzVgvwyALBrKA/w640-h362/wdfwf.JPG" alt="" width="640" height="362" border="0" data-original-height="427" data-original-width="754" /></a> </div> <p style="text-align: justify;"><strong><u><a href="https://sale365day.com/get-billionnaire-brain" target="_blank" rel="nofollow noopener"><span style="font-size: large;">Click Here To Purchase Billionaire Brain Wave Program at official website</span></a></u></strong></p> <h2 style="text-align: justify;"><strong>Frequently Asked Questions</strong></h2> <p style="text-align: justify;"><strong>How long is the audio track of Billionaire Brain Wave?</strong></p> <p style="text-align: justify;">The audio track of <a href="https://medium.com/@brainwavenew">Billionaire Brain Wave</a> is 7 minutes long.</p> <p style="text-align: justify;"><strong>Is it necessary to listen to the Billionaire Brain Wave audio tracking using earbuds?</strong></p> <p style="text-align: justify;">The creator of <a href="https://sketchfab.com/3d-models/billionaire-brain-wave-is-it-legit-2023-expose-6eebc7bf56a14709b5fca6d7c7264d3b">Billionaire Brain Wave</a> suggests that you listen to it with earbuds or headphones instead of playing it out loud.</p> <p style="text-align: justify;"><strong>How to get access to the Billionaire Brain Wave audio track?</strong></p> <p style="text-align: justify;">You can now get access to the <a href="https://www.facebook.com/profile.php?id=61550158719435">Billionaire Brain Wave</a> on the official website of the program. Just complete the order process and then you can download the audio track to your device.</p> <p style="text-align: justify;"><strong>How long should I listen to the Billionaire Brain Wave audio track?</strong></p> <p style="text-align: justify;">The creator of <a href="https://zee-news-report.clubeo.com/page/billionaire-brain-wave-shocking-information-leaked-by-customers-does-it-really-works.html">Billionaire Brain Wave</a> says that the time needed to get results from listening to the audio track may vary from person to person. But the majority of the users were able to get results after a few months of listening to the audio track consistently.</p> <p style="text-align: justify;"><strong>What to do if Billionaire Brain Wave does not work for me?</strong></p> <p style="text-align: justify;">If Billionaire Brain Wave does not work for you, you can request a refund from the creator of the program within 90 days of accessing it from the official website.</p> <p style="text-align: justify;">First things first, let&rsquo;s start with discussing what <a href="https://vocal.media/stories/billionaire-brain-wave-100-trusted-is-it-proven-or-fake-money-booster">Billionaire Brain Wave</a> is. The program, <a href="https://billionaire-brain-wave-official.jimdosite.com/">Billionaire Brain Wave</a>, is created to help people achieve their true and maximum potential by providing them with the audio frequencies needed to activate the Theta brain wave. By doing this, Billionaire Brain Wave is supporting you in attaining all the wealth and happiness that you need in your life.</p> <p><strong>Read More:</strong></p> <p><a href="https://fit-breath.blogspot.com/2023/08/billionaire-brain-wave.html">https://fit-breath.blogspot.com/2023/08/billionaire-brain-wave.html</a><br /><a href="https://billionaire-brain-wave-official.jimdosite.com/">https://billionaire-brain-wave-official.jimdosite.com/</a><br /><a href="https://www.fuzia.com/article_detail/799343/billionaire-brain-wave-2023-dont-buy-till-you-read-thi">https://www.fuzia.com/article_detail/799343/billionaire-brain-wave-2023-dont-buy-till-you-read-thi</a><br /><a href="https://www.forexagone.com/forum/experiences-trading/billionaire-brain-wave-update-warning-know-the-truth-behind-this-before-buying-58200#155335">https://www.forexagone.com/forum/experiences-trading/billionaire-brain-wave-update-warning-know-the-truth-behind-this-before-buying-58200#155335</a><br /><a href="https://www.fuzia.com/fz/billionaire-brain-wave">https://www.fuzia.com/fz/billionaire-brain-wave</a><br /><a href="https://soundcloud.com/billionaire-brain-wave/billionaire-brain-wave-scientifically-proven-that-attracts-money-effortlessly">https://soundcloud.com/billionaire-brain-wave/billionaire-brain-wave-scientifically-proven-that-attracts-money-effortlessly</a><br /><a href="https://billionairebrainwaveupdate.bandcamp.com/track/billionaire-brain-wave-fraud-alert-2023-is-it-really-attracts-money-or-fake-claim">https://billionairebrainwaveupdate.bandcamp.com/track/billionaire-brain-wave-fraud-alert-2023-is-it-really-attracts-money-or-fake-claim</a><br /><a href="https://billionairebrainwaveupdate.contently.com/">https://billionairebrainwaveupdate.contently.com/</a><br /><a href="https://zee-news-report.clubeo.com/page/billionaire-brain-wave-shocking-information-leaked-by-customers-does-it-really-works.html">https://zee-news-report.clubeo.com/page/billionaire-brain-wave-shocking-information-leaked-by-customers-does-it-really-works.html</a><br /><a href="https://groups.google.com/g/billionaire-brain-wave-update">https://groups.google.com/g/billionaire-brain-wave-update</a><br /><a href="https://groups.google.com/g/billionaire-brain-wave-update/c/JqttphVTJ7A">https://groups.google.com/g/billionaire-brain-wave-update/c/JqttphVTJ7A</a><br /><a href="https://groups.google.com/g/billionaire-brain-wave-update/c/b9WfzqtTYvQ">https://groups.google.com/g/billionaire-brain-wave-update/c/b9WfzqtTYvQ</a><br /><a href="https://billionaire-brain-wave-2023.webflow.io/">https://billionaire-brain-wave-2023.webflow.io/</a><br /><a href="https://colab.research.google.com/drive/1M4sGwm3y0cKd5bDrn5hkBurfT5BrytMy">https://colab.research.google.com/drive/1M4sGwm3y0cKd5bDrn5hkBurfT5BrytMy</a><br /><a href="https://lookerstudio.google.com/reporting/9cb64507-5056-4650-87e5-07704a76c13a/page/f6GaD">https://lookerstudio.google.com/reporting/9cb64507-5056-4650-87e5-07704a76c13a/page/f6GaD</a><br /><a href="https://infogram.com/billionaire-brain-wave-program-scientifically-proven-by-four-neuroscience-labs-that-attracts-money-effortlessly-1hdw2jpommdqj2l?live">https://infogram.com/billionaire-brain-wave-program-scientifically-proven-by-four-neuroscience-labs-that-attracts-money-effortlessly-1hdw2jpommdqj2l?live</a><br /><a href="https://devfolio.co/@billionairewave">https://devfolio.co/@billionairewave</a><br /><a href="https://billionaire-brain-wave-update.hashnode.dev/billionaire-brain-wave-program-scientifically-proven-that-attracts-money-effortlessly">https://billionaire-brain-wave-update.hashnode.dev/billionaire-brain-wave-program-scientifically-proven-that-attracts-money-effortlessly</a><br /><a href="https://medium.com/@brainwavenew/billionaire-brain-wave-program-scientifically-proven-by-labs-that-attracts-money-effortlessly-8f01437db9ee">https://medium.com/@brainwavenew/billionaire-brain-wave-program-scientifically-proven-by-labs-that-attracts-money-effortlessly-8f01437db9ee</a><br /><a href="https://medium.com/@brainwavenew">https://medium.com/@brainwavenew</a><br /><a href="https://sketchfab.com/3d-models/billionaire-brain-wave-is-it-legit-2023-expose-6eebc7bf56a14709b5fca6d7c7264d3b">https://sketchfab.com/3d-models/billionaire-brain-wave-is-it-legit-2023-expose-6eebc7bf56a14709b5fca6d7c7264d3b</a><br /><a href="https://www.facebook.com/profile.php?id=61550158719435">https://www.facebook.com/profile.php?id=61550158719435</a><br /><a href="https://billionairebrainwave.godaddysites.com/">https://billionairebrainwave.godaddysites.com/</a><br /><a href="https://www.protocols.io/blind/31E0F4043E7C11EEB0D10A58A9FEAC02">https://www.protocols.io/blind/31E0F4043E7C11EEB0D10A58A9FEAC02</a><br /><a href="https://www.provenexpert.com/billionaire-brain-wave-program/">https://www.provenexpert.com/billionaire-brain-wave-program/</a><br /><a href="https://www.townscript.com/e/billionaire-brain-wave-program-warning-scam-exposed-does-it-work-014021">https://www.townscript.com/e/billionaire-brain-wave-program-warning-scam-exposed-does-it-work-014021</a><br /><a href="https://vocal.media/stories/billionaire-brain-wave-100-trusted-is-it-proven-or-fake-money-booster">https://vocal.media/stories/billionaire-brain-wave-100-trusted-is-it-proven-or-fake-money-booster</a><br /><a href="https://billionaire-brain-wave-program.company.site/">https://billionaire-brain-wave-program.company.site/</a><br /><a href="https://www.forexagone.com/forum/journal-de-trading/billionaire-brain-wave-reviews-scientifically-proven-by-four-neuroscience-labs-that-attracts-money-effortlessly-58458#155593">https://www.forexagone.com/forum/journal-de-trading/billionaire-brain-wave-reviews-scientifically-proven-by-four-neuroscience-labs-that-attracts-money-effortlessly-58458#155593</a><br /><a href="https://billionairebrainwavereport.bandcamp.com/track/billionaire-brain-wave-reviews-update-is-it-really-helps-to-boost-wealth-money-quickly">https://billionairebrainwavereport.bandcamp.com/track/billionaire-brain-wave-reviews-update-is-it-really-helps-to-boost-wealth-money-quickly</a><br /><a href="https://sketchfab.com/3d-models/billionaire-brain-wave-reviews-2023-1program-72068cc329b843e393ab46f8aa6bcb56">https://sketchfab.com/3d-models/billionaire-brain-wave-reviews-2023-1program-72068cc329b843e393ab46f8aa6bcb56</a><br /><a href="https://billionairebrainwavereport.contently.com/">https://billionairebrainwavereport.contently.com/</a><br /><a href="https://www.fuzia.com/article_detail/799386/billionaire-brain-wave-program-reviews-the-reality-here">https://www.fuzia.com/article_detail/799386/billionaire-brain-wave-program-reviews-the-reality-here</a><br /><a href="https://news-clicks-report.clubeo.com/page/billionaire-brain-wave-reviews-scientifically-proven-by-four-neuroscience-labs-that-attracts-money-effortlessly.html">https://news-clicks-report.clubeo.com/page/billionaire-brain-wave-reviews-scientifically-proven-by-four-neuroscience-labs-that-attracts-money-effortlessly.html</a></p>
krishi/clothing
2023-08-19T12:35:25.000Z
[ "region:us" ]
krishi
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 41259319.0 num_examples: 20 download_size: 41261925 dataset_size: 41259319.0 --- # Dataset Card for "clothing" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
tThreshold/modelsthatareNOTmadebymeiREPOSTEDthesebecauseTHEIRLINKSAREBROKEN
2023-09-20T07:00:23.000Z
[ "license:openrail", "region:us" ]
tThreshold
null
null
null
0
0
--- license: openrail ---
aviroes/elderly_CV
2023-08-19T12:43:32.000Z
[ "region:us" ]
aviroes
null
null
null
0
0
--- dataset_info: features: - name: client_id dtype: string - name: path dtype: string - name: audio dtype: audio: sampling_rate: 48000 - name: sentence dtype: string - name: up_votes dtype: int64 - name: down_votes dtype: int64 - name: age dtype: string - name: gender dtype: string - name: accent dtype: string - name: locale dtype: string - name: segment dtype: string splits: - name: train num_bytes: 432633690.18249494 num_examples: 12237 download_size: 547583971 dataset_size: 432633690.18249494 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "elderly_CV" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
BaekRok/vishing_data_2
2023-08-19T14:26:23.000Z
[ "region:us" ]
BaekRok
null
null
null
0
0
Entry not found
gwj/tinali
2023-08-19T13:15:42.000Z
[ "region:us" ]
gwj
null
null
null
0
0
Entry not found
NarchAI1992/townhouse
2023-08-19T14:11:53.000Z
[ "license:openrail", "region:us" ]
NarchAI1992
null
null
null
0
0
--- license: openrail ---
longquan/llm-japanese-dataset-split_10
2023-08-19T13:51:20.000Z
[ "task_categories:question-answering", "size_categories:100K<n<1M", "language:ja", "language:en", "license:cc-by-sa-4.0", "region:us" ]
longquan
null
null
null
0
0
--- license: cc-by-sa-4.0 task_categories: - question-answering language: - ja - en size_categories: - 100K<n<1M ---
am-not-a-scientist/test1
2023-08-19T13:53:39.000Z
[ "license:unknown", "region:us" ]
am-not-a-scientist
null
null
null
0
0
--- license: unknown ---
samxm111/rlhf-reward-single-round
2023-08-19T14:24:50.000Z
[ "region:us" ]
samxm111
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: prompt dtype: string - name: chosen dtype: string - name: rejected dtype: string splits: - name: train num_bytes: 13533459 num_examples: 20000 - name: test num_bytes: 3460316 num_examples: 5014 download_size: 0 dataset_size: 16993775 --- # Dataset Card for "rlhf-reward-single-round" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
marasama/nva-chirico_cuvie
2023-08-20T23:33:49.000Z
[ "region:us" ]
marasama
null
null
null
0
0
Entry not found
VinVanGogh/Psychology-10K-Indo-Llama2-Chat
2023-08-22T14:58:06.000Z
[ "region:us" ]
VinVanGogh
null
null
null
2
0
Entry not found
Dippi9845/arxiv_with_fragments
2023-08-25T09:02:20.000Z
[ "region:us" ]
Dippi9845
null
null
null
0
0
Entry not found
Dippi9845/cnn_with_fragments
2023-08-25T09:09:30.000Z
[ "license:apache-2.0", "region:us" ]
Dippi9845
null
null
null
0
0
--- license: apache-2.0 ---
Back-up/test-argilla
2023-08-19T14:42:27.000Z
[ "size_categories:1K<n<10K", "rlfh", "argilla", "human-feedback", "region:us" ]
Back-up
null
null
null
0
0
--- size_categories: 1K<n<10K tags: - rlfh - argilla - human-feedback --- # Dataset Card for test-argilla This dataset has been created with [Argilla](https://docs.argilla.io). As shown in the sections below, this dataset can be loaded into Argilla as explained in [Load with Argilla](#load-with-argilla), or used directly with the `datasets` library in [Load with `datasets`](#load-with-datasets). ## Dataset Description - **Homepage:** https://argilla.io - **Repository:** https://github.com/argilla-io/argilla - **Paper:** - **Leaderboard:** - **Point of Contact:** ### Dataset Summary This dataset contains: * A dataset configuration file conforming to the Argilla dataset format named `argilla.yaml`. This configuration file will be used to configure the dataset when using the `FeedbackDataset.from_huggingface` method in Argilla. * Dataset records in a format compatible with HuggingFace `datasets`. These records will be loaded automatically when using `FeedbackDataset.from_huggingface` and can be loaded independently using the `datasets` library via `load_dataset`. * The [annotation guidelines](#annotation-guidelines) that have been used for building and curating the dataset, if they've been defined in Argilla. ### Load with Argilla To load with Argilla, you'll just need to install Argilla as `pip install argilla --upgrade` and then use the following code: ```python import argilla as rg ds = rg.FeedbackDataset.from_huggingface("Back-up/test-argilla") ``` ### Load with `datasets` To load this dataset with `datasets`, you'll just need to install `datasets` as `pip install datasets --upgrade` and then use the following code: ```python from datasets import load_dataset ds = load_dataset("Back-up/test-argilla") ``` ### Supported Tasks and Leaderboards This dataset can contain [multiple fields, questions and responses](https://docs.argilla.io/en/latest/guides/llms/conceptual_guides/data_model.html) so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the [Dataset Structure section](#dataset-structure). There are no leaderboards associated with this dataset. ### Languages [More Information Needed] ## Dataset Structure ### Data in Argilla The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, and **guidelines**. The **fields** are the dataset records themselves, for the moment just text fields are suppported. These are the ones that will be used to provide responses to the questions. | Field Name | Title | Type | Required | Markdown | | ---------- | ----- | ---- | -------- | -------- | | question | Question | TextField | True | False | | answer | Answer | TextField | True | False | The **questions** are the questions that will be asked to the annotators. They can be of different types, such as rating, text, single choice, or multiple choice. | Question Name | Title | Type | Required | Description | Values/Labels | | ------------- | ----- | ---- | -------- | ----------- | ------------- | | answer_quality | Answer_quality | RatingQuestion | True | How would you rate the quality of the answer? | [1, 2, 3, 4, 5] | | answer_correction | Answer_correction | TextQuestion | False | If you think the answer is not accurate, please, correct it. | N/A | **✨ NEW** Additionally, we also have **suggestions**, which are linked to the existing questions, and so on, named appending "-suggestion" and "-suggestion-metadata" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above. Finally, the **guidelines** are just a plain string that can be used to provide instructions to the annotators. Find those in the [annotation guidelines](#annotation-guidelines) section. ### Data Instances An example of a dataset instance in Argilla looks as follows: ```json { "fields": { "answer": "Camels use the fat in their humps to keep them filled with energy and hydration for long periods of time.", "question": "Why can camels survive for long without water?" }, "metadata": {}, "responses": [ { "status": "submitted", "user_id": "dfda9e47-cd98-4c76-9cf8-2595da8d593b", "values": { "answer_correction": { "value": "hello" }, "answer_quality": { "value": 2 } } } ], "suggestions": [] } ``` While the same record in HuggingFace `datasets` looks as follows: ```json { "answer": "Michael Phelps has won the most gold medals of all time with 23 golds.", "answer_correction": [], "answer_correction-suggestion": null, "answer_correction-suggestion-metadata": { "agent": null, "score": null, "type": null }, "answer_quality": [], "answer_quality-suggestion": null, "answer_quality-suggestion-metadata": { "agent": null, "score": null, "type": null }, "external_id": null, "metadata": "{}", "question": "What individual has won the most Olympic gold medals in the history of the games?" } ``` ### Data Fields Among the dataset fields, we differentiate between the following: * **Fields:** These are the dataset records themselves, for the moment just text fields are suppported. These are the ones that will be used to provide responses to the questions. * **question** is of type `TextField`. * **answer** is of type `TextField`. * **Questions:** These are the questions that will be asked to the annotators. They can be of different types, such as `RatingQuestion`, `TextQuestion`, `LabelQuestion`, `MultiLabelQuestion`, and `RankingQuestion`. * **answer_quality** is of type `RatingQuestion` with the following allowed values [1, 2, 3, 4, 5], and description "How would you rate the quality of the answer?". * (optional) **answer_correction** is of type `TextQuestion`, and description "If you think the answer is not accurate, please, correct it.". * **✨ NEW** **Suggestions:** As of Argilla 1.13.0, the suggestions have been included to provide the annotators with suggestions to ease or assist during the annotation process. Suggestions are linked to the existing questions, are always optional, and contain not just the suggestion itself, but also the metadata linked to it, if applicable. * (optional) **answer_quality-suggestion** is of type `rating` with the following allowed values [1, 2, 3, 4, 5]. * (optional) **answer_correction-suggestion** is of type `text`. Additionally, we also have one more field which is optional and is the following: * **external_id:** This is an optional field that can be used to provide an external ID for the dataset record. This can be useful if you want to link the dataset record to an external resource, such as a database or a file. ### Data Splits The dataset contains a single split, which is `train`. ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation guidelines Please, read the question carefully and try to answer it as accuracy as possible. #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]
Chanblock/250_remates
2023-08-19T14:56:32.000Z
[ "region:us" ]
Chanblock
null
null
null
0
0
Entry not found
aviroes/mascir_elderly_voice
2023-08-19T14:57:14.000Z
[ "region:us" ]
aviroes
null
null
null
1
0
--- dataset_info: features: - name: client_id dtype: string - name: path dtype: string - name: audio dtype: audio: sampling_rate: 48000 - name: sentence dtype: string - name: up_votes dtype: int64 - name: down_votes dtype: int64 - name: age dtype: string - name: gender dtype: string - name: accent dtype: string - name: locale dtype: string - name: segment dtype: string splits: - name: validated num_bytes: 744166102.2652498 num_examples: 21211 download_size: 877313436 dataset_size: 744166102.2652498 configs: - config_name: default data_files: - split: validated path: data/validated-* --- # Dataset Card for "mascir_elderly_voice" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)