datasetId
stringlengths 2
117
| author
stringlengths 2
42
⌀ | last_modified
timestamp[us, tz=UTC] | downloads
int64 0
9.36M
| likes
int64 0
3.89k
| tags
sequence | task_categories
sequence | createdAt
timestamp[us, tz=UTC] | card
stringlengths 19
1.01M
| embedding
sequence |
|---|---|---|---|---|---|---|---|---|---|
benayas/banking_llm_v5 | benayas | 2023-12-13T02:31:13Z | 4 | 0 | [
"region:us"
] | null | 2023-12-13T02:31:10Z | ---
dataset_info:
features:
- name: text
dtype: string
- name: category
dtype: string
splits:
- name: train
num_bytes: 28215739
num_examples: 10003
- name: test
num_bytes: 8667330
num_examples: 3080
download_size: 3163292
dataset_size: 36883069
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
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] |
Seongill/NQ_5_adversary | Seongill | 2023-12-13T06:15:23Z | 4 | 0 | [
"region:us"
] | null | 2023-12-13T06:15:08Z | ---
dataset_info:
features:
- name: question
dtype: string
- name: answers
sequence: string
- name: ctxs
list:
- name: answer_sent
sequence: string
- name: hasanswer
dtype: bool
- name: id
dtype: string
- name: score
dtype: float64
- name: text
dtype: string
- name: title
dtype: string
- name: has_answer
dtype: bool
- name: random_sub
dtype: string
- name: similar_sub
dtype: string
- name: ent_type
dtype: string
- name: new_ctxs
list:
- name: answer_sent
sequence: string
- name: hasanswer
dtype: bool
- name: id
dtype: string
- name: is_adv
dtype: bool
- name: new_answer_sent
dtype: string
- name: original_text
dtype: string
- name: score
dtype: float64
- name: text
dtype: string
- name: title
dtype: string
- name: num_advs
dtype: int64
- name: num_ctxs
dtype: int64
splits:
- name: train
num_bytes: 27454991
num_examples: 3610
download_size: 15657266
dataset_size: 27454991
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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Seongill/NQ_5_adversary_v3 | Seongill | 2023-12-13T06:52:10Z | 4 | 0 | [
"region:us"
] | null | 2023-12-13T06:52:05Z | ---
dataset_info:
features:
- name: question
dtype: string
- name: answers
sequence: string
- name: has_answer
dtype: bool
- name: similar_sub
dtype: string
- name: ctxs
list:
- name: answer_sent
sequence: string
- name: hasanswer
dtype: bool
- name: id
dtype: string
- name: is_adv
dtype: bool
- name: new_answer_sent
dtype: string
- name: original_text
dtype: string
- name: score
dtype: float64
- name: text
dtype: string
- name: title
dtype: string
- name: num_advs
dtype: int64
splits:
- name: train
num_bytes: 14326455
num_examples: 3610
download_size: 7639062
dataset_size: 14326455
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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sproos/summeval-fr | sproos | 2023-12-13T22:40:46Z | 4 | 0 | [
"region:us"
] | null | 2023-12-13T17:46:54Z | ---
dataset_info:
features:
- name: machine_summaries
sequence: string
- name: human_summaries
sequence: string
- name: relevance
sequence: float64
- name: coherence
sequence: float64
- name: fluency
sequence: float64
- name: consistency
sequence: float64
- name: text
dtype: string
- name: id
dtype: string
splits:
- name: train
num_bytes: 1276634
num_examples: 100
download_size: 503320
dataset_size: 1276634
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "summeval-fr"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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sproos/summeval-es | sproos | 2023-12-13T22:40:42Z | 4 | 0 | [
"region:us"
] | null | 2023-12-13T17:47:07Z | ---
dataset_info:
features:
- name: machine_summaries
sequence: string
- name: human_summaries
sequence: string
- name: relevance
sequence: float64
- name: coherence
sequence: float64
- name: fluency
sequence: float64
- name: consistency
sequence: float64
- name: text
dtype: string
- name: id
dtype: string
splits:
- name: train
num_bytes: 1232365
num_examples: 100
download_size: 485176
dataset_size: 1232365
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "summeval-es"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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davidgaofc/shadow_inout_clean | davidgaofc | 2023-12-14T03:08:56Z | 4 | 0 | [
"region:us"
] | null | 2023-12-13T18:25:02Z | ---
dataset_info:
features:
- name: Text
dtype: string
- name: Label
dtype: int64
splits:
- name: train
num_bytes: 790055
num_examples: 1640
download_size: 345224
dataset_size: 790055
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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davidgaofc/RM_inout_clean | davidgaofc | 2023-12-14T03:09:20Z | 4 | 0 | [
"region:us"
] | null | 2023-12-13T18:26:32Z | ---
dataset_info:
features:
- name: Text
dtype: string
- name: Label
dtype: int64
splits:
- name: train
num_bytes: 781877
num_examples: 1640
download_size: 346257
dataset_size: 781877
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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alirezaomneky/background-model | alirezaomneky | 2023-12-13T20:50:45Z | 4 | 0 | [
"region:us"
] | null | 2023-12-13T20:50:43Z | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 7921068.0
num_examples: 8
download_size: 7922945
dataset_size: 7921068.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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ctam8736/papi_asr_mini | ctam8736 | 2023-12-13T21:55:29Z | 4 | 0 | [
"license:mit",
"region:us"
] | null | 2023-12-13T21:53:19Z | ---
license: mit
dataset_info:
features:
- name: audio
dtype: audio
- name: transcript
dtype: string
splits:
- name: train
num_bytes: 19144271.21495327
num_examples: 85
- name: test
num_bytes: 4207914.785046729
num_examples: 22
download_size: 22633018
dataset_size: 23352186.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
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vivekdugale/llama2_mental_health_conversations_smaller_dataset | vivekdugale | 2023-12-14T06:45:06Z | 4 | 0 | [
"region:us"
] | null | 2023-12-14T06:37:37Z | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 459521
num_examples: 346
download_size: 243309
dataset_size: 459521
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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kowndinya23/cot-submix-llama-2-13b-2048 | kowndinya23 | 2023-12-14T10:34:39Z | 4 | 0 | [
"region:us"
] | null | 2023-12-14T10:34:22Z | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: inputs
dtype: string
- name: targets
dtype: string
- name: task_source
dtype: string
- name: task_name
dtype:
class_label:
names:
'0': cot_creak
'1': cot_creak_ii
'2': cot_ecqa
'3': cot_ecqa_ii
'4': cot_esnli
'5': cot_esnli_ii
'6': cot_gsm8k
'7': cot_gsm8k_ii
'8': cot_qasc
'9': cot_qasc_ii
'10': cot_sensemaking
'11': cot_sensemaking_ii
'12': cot_strategyqa
'13': cot_strategyqa_ii
'14': stream_aqua
'15': stream_aqua_ii
'16': stream_qed
'17': stream_qed_ii
- name: template_type
dtype: string
splits:
- name: train
num_bytes: 205165842.1236458
num_examples: 181945
- name: validation
num_bytes: 2072575.8763541786
num_examples: 1838
download_size: 100101232
dataset_size: 207238418.0
---
# Dataset Card for "cot-submix-llama-2-13b-2048"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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kowndinya23/dialog-submix-llama-2-13b-2048 | kowndinya23 | 2023-12-14T10:36:43Z | 4 | 0 | [
"region:us"
] | null | 2023-12-14T10:35:49Z | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: inputs
dtype: string
- name: targets
dtype: string
- name: task_source
dtype: string
- name: task_name
dtype:
class_label:
names:
'0': qrecc
'1': qrecc_ii
'2': wiki_dialog
'3': wiki_dialog_ii
- name: template_type
dtype: string
splits:
- name: train
num_bytes: 1009790862.7760382
num_examples: 548274
- name: validation
num_bytes: 10201526.223961879
num_examples: 5539
download_size: 584835149
dataset_size: 1019992389.0
---
# Dataset Card for "dialog-submix-llama-2-13b-2048"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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abhishek/autotrain-data-2lcs-vv9d-tssd | abhishek | 2023-12-14T13:25:03Z | 4 | 0 | [
"region:us"
] | null | 2023-12-14T13:24:40Z | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': daisy
'1': dandelion
'2': rose
'3': sunflower
'4': tulip
splits:
- name: train
num_bytes: 114899538.888
num_examples: 2196
- name: validation
num_bytes: 33595965.0
num_examples: 550
download_size: 167022637
dataset_size: 148495503.888
---
# Dataset Card for "autotrain-data-2lcs-vv9d-tssd"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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abhishek/autotrain-data-2lld-7hpl-t0wr | abhishek | 2023-12-14T13:32:26Z | 4 | 0 | [
"region:us"
] | null | 2023-12-14T13:32:04Z | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': daisy
'1': dandelion
'2': rose
'3': sunflower
'4': tulip
splits:
- name: train
num_bytes: 114899538.888
num_examples: 2196
- name: validation
num_bytes: 33595965.0
num_examples: 550
download_size: 167022637
dataset_size: 148495503.888
---
# Dataset Card for "autotrain-data-2lld-7hpl-t0wr"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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] |
ctang/HarmfulVsEthical_redteaming_eval_v3 | ctang | 2023-12-14T14:58:53Z | 4 | 0 | [
"region:us"
] | null | 2023-12-14T14:58:52Z | ---
dataset_info:
features:
- name: prompt
dtype: string
- name: response_a
dtype: string
- name: response_b
dtype: string
- name: more_reasonable
dtype: string
splits:
- name: train
num_bytes: 617846
num_examples: 254
download_size: 315012
dataset_size: 617846
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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oskarvanderwal/simple-cooccurrence-bias | oskarvanderwal | 2023-12-14T15:58:03Z | 4 | 0 | [
"license:mit",
"region:us"
] | null | 2023-12-14T15:32:13Z | ---
license: mit
---
`simple-cooccurrence-bias` contains the sentences used in the simple cooccurrence (or association) test used for evaluating gender bias originally proposed for GPT-3 (Brown et al., 2020).
This dataset is based on the details described in "Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model" (Smith et al., 2022). | [
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adhisetiawan/bdd10k-colormaps | adhisetiawan | 2023-12-14T16:06:26Z | 4 | 0 | [
"region:us"
] | null | 2023-12-14T15:57:09Z | ---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype: image
splits:
- name: train
num_bytes: 856755130.0
num_examples: 7000
- name: validation
num_bytes: 157758418.0
num_examples: 1000
download_size: 980161348
dataset_size: 1014513548.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
---
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davidgaofc/PriMa5_inout_clean | davidgaofc | 2023-12-14T21:18:27Z | 4 | 0 | [
"region:us"
] | null | 2023-12-14T21:12:32Z | ---
dataset_info:
features:
- name: Text
dtype: string
- name: Label
dtype: int64
splits:
- name: train
num_bytes: 809188
num_examples: 910
download_size: 313284
dataset_size: 809188
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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] |
Xapien/ER_potentially_missed_entities | Xapien | 2023-12-15T13:44:04Z | 4 | 0 | [
"region:us"
] | null | 2023-12-15T11:57:53Z | ---
dataset_info:
features:
- name: text
dtype: string
- name: potentially_missed_ents
sequence: string
- name: source_edges
sequence:
sequence: string
- name: original_ents
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 1932486
num_examples: 229
download_size: 594424
dataset_size: 1932486
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "ER_potentially_missed_entities"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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BlahBlah314/AcolyteTxE | BlahBlah314 | 2023-12-15T13:12:28Z | 4 | 0 | [
"region:us"
] | null | 2023-12-15T13:12:26Z | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: transcription
dtype: string
- name: enhanced
dtype: string
splits:
- name: train
num_bytes: 443879
num_examples: 279
download_size: 94412
dataset_size: 443879
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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] |
arieg/cluster_cls | arieg | 2023-12-15T13:48:01Z | 4 | 0 | [
"region:us"
] | null | 2023-12-15T13:46:09Z | ---
dataset_info:
features:
- name: image
dtype: image
- name: track_id
dtype:
class_label:
names:
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'1': '000005'
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- name: label
dtype: int64
splits:
- name: train
num_bytes: 2137269729.0
num_examples: 39985
download_size: 2117712815
dataset_size: 2137269729.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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kunishou/do-not-answer-ja-120 | kunishou | 2023-12-15T17:26:07Z | 4 | 0 | [
"license:cc-by-nc-sa-4.0",
"region:us"
] | null | 2023-12-15T17:17:00Z | ---
license: cc-by-nc-sa-4.0
---
This dataset was created by automatically translating "do-not-answer" into Japanese.
This dataset is licensed under CC-BY-NC-SA-4.0
Do-Not-Answer-Ja の 12 の有害カテゴリから 10 レコードずつピックアップした簡易評価版です。
Do-Not-Answer-Ja の 939 レコードで評価すると OpenAI API コストや評価時間を短縮することが可能です。
| |Do-Not-Answer-Ja|Do-Not-Answer-Ja-120|
|:----|:----|:----|
|Num Records|939|120|
|OpenAI API コスト|6,000 円 / モデル|700 円 / モデル|
|応答生成 / 評価時間|10時間 / モデル|1時間 / モデル|
do-not-answer-ja
https://github.com/kunishou/do-not-answer-ja
do-not-answer
https://github.com/Libr-AI/do-not-answer | [
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TinyPixel/elm-sys | TinyPixel | 2023-12-16T13:25:56Z | 4 | 0 | [
"region:us"
] | null | 2023-12-16T04:14:15Z | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 2591217
num_examples: 1073
download_size: 1394627
dataset_size: 2591217
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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DragonLine/ksponspeech_05 | DragonLine | 2023-12-16T15:35:46Z | 4 | 0 | [
"region:us"
] | null | 2023-12-16T15:18:52Z | ---
dataset_info:
features:
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: transcripts
dtype: string
splits:
- name: train
num_bytes: 18234945060.0
num_examples: 101236
- name: test
num_bytes: 2410514563.634364
num_examples: 12655
- name: valid
num_bytes: 2300143023.7636356
num_examples: 12654
download_size: 21259055664
dataset_size: 22945602647.398003
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: valid
path: data/valid-*
---
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asmaa-ali/llama-2-instruct-SaferSkin-V1 | asmaa-ali | 2023-12-17T11:11:23Z | 4 | 0 | [
"region:us"
] | null | 2023-12-16T21:13:30Z | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 190691
num_examples: 1222
download_size: 33205
dataset_size: 190691
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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cheafdevo56/InfluentialTriplets10Percent | cheafdevo56 | 2023-12-17T05:09:51Z | 4 | 0 | [
"region:us"
] | null | 2023-12-17T05:09:44Z | ---
dataset_info:
features:
- name: query
struct:
- name: abstract
dtype: string
- name: corpus_id
dtype: int64
- name: title
dtype: string
- name: pos
struct:
- name: abstract
dtype: string
- name: corpus_id
dtype: int64
- name: title
dtype: string
- name: neg
struct:
- name: abstract
dtype: string
- name: corpus_id
dtype: int64
- name: score
dtype: int64
- name: title
dtype: string
splits:
- name: train
num_bytes: 173168883.9
num_examples: 45000
- name: validation
num_bytes: 19240987.1
num_examples: 5000
download_size: 115719612
dataset_size: 192409871.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
---
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ChayanM/mimic-QA-llama2-121k_train_test | ChayanM | 2023-12-17T06:37:56Z | 4 | 0 | [
"region:us"
] | null | 2023-12-17T06:37:53Z | ---
dataset_info:
features:
- name: QA
dtype: string
splits:
- name: train
num_bytes: 54391024.52637656
num_examples: 109119
- name: test
num_bytes: 6043779.473623437
num_examples: 12125
download_size: 21179351
dataset_size: 60434804.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
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metric-space/experiment_med | metric-space | 2023-12-17T06:52:35Z | 4 | 0 | [
"region:us"
] | null | 2023-12-17T06:52:32Z | ---
dataset_info:
features:
- name: meta_info
dtype: string
- name: question
dtype: string
- name: answer_idx
dtype: string
- name: answer
dtype: string
- name: options
list:
- name: key
dtype: string
- name: value
dtype: string
splits:
- name: part1
num_bytes: 3258966
num_examples: 3392
- name: part2
num_bytes: 3242635
num_examples: 3392
- name: part3
num_bytes: 3263765
num_examples: 3394
download_size: 5353119
dataset_size: 9765366
configs:
- config_name: default
data_files:
- split: part1
path: data/part1-*
- split: part2
path: data/part2-*
- split: part3
path: data/part3-*
---
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ayan1988/diffusion.maobi2 | ayan1988 | 2023-12-17T13:29:51Z | 4 | 0 | [
"region:us"
] | null | 2023-12-17T12:43:07Z | ---
dataset_info:
features:
- name: image
dtype: image
- name: conditioning_image
dtype: image
- name: txt
dtype: string
splits:
- name: train
num_bytes: 15526635.0
num_examples: 319
download_size: 14468827
dataset_size: 15526635.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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RahulRaman/counting-object-sd-dataset5-clean5 | RahulRaman | 2023-12-17T14:11:22Z | 4 | 0 | [
"region:us"
] | null | 2023-12-17T14:11:15Z | ---
dataset_info:
features:
- name: input_image
dtype: image
- name: edit_prompt
dtype: string
- name: edited_image
dtype: image
splits:
- name: train
num_bytes: 47253801.0
num_examples: 496
download_size: 23715117
dataset_size: 47253801.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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themanas021/MATH-Algebra | themanas021 | 2023-12-17T16:29:57Z | 4 | 0 | [
"license:mit",
"region:us"
] | null | 2023-12-17T15:07:00Z | ---
license: mit
---
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rinormaloku/test | rinormaloku | 2023-12-17T15:08:11Z | 4 | 0 | [
"license:mit",
"region:us"
] | null | 2023-12-17T15:07:37Z | ---
license: mit
dataset_info:
features:
- name: instruction
dtype: string
- name: input
dtype: string
- name: output
dtype: string
- name: text
dtype: string
splits:
- name: train
num_bytes: 427762
num_examples: 300
download_size: 238327
dataset_size: 427762
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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vigneshgs7/Boundary_detection_onelasttry | vigneshgs7 | 2023-12-17T15:16:57Z | 4 | 0 | [
"region:us"
] | null | 2023-12-17T15:16:30Z | ---
dataset_info:
features:
- name: pixel_values
dtype: image
- name: label
dtype: image
splits:
- name: train
num_bytes: 1242702805.0
num_examples: 25
download_size: 32579261
dataset_size: 1242702805.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "Boundary_detection_onelasttry"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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greathero/newcontrailsvalidationdataset | greathero | 2023-12-17T18:50:48Z | 4 | 0 | [
"region:us"
] | null | 2023-12-17T16:08:14Z | ---
dataset_info:
features:
- name: pixel_values
dtype: image
- name: label
dtype: image
splits:
- name: train
num_bytes: 325995028.72
num_examples: 16695
download_size: 319405984
dataset_size: 325995028.72
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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NobodyExistsOnTheInternet/sysmsgalpacatest | NobodyExistsOnTheInternet | 2023-12-17T17:14:29Z | 4 | 0 | [
"license:mit",
"region:us"
] | null | 2023-12-17T16:36:46Z | ---
license: mit
---
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] |
raoel/datasets-github-issues | raoel | 2023-12-17T17:03:40Z | 4 | 0 | [
"region:us"
] | null | 2023-12-17T17:03:37Z | ---
dataset_info:
features:
- name: url
dtype: string
- name: repository_url
dtype: string
- name: labels_url
dtype: string
- name: comments_url
dtype: string
- name: events_url
dtype: string
- name: html_url
dtype: string
- name: id
dtype: int64
- name: node_id
dtype: string
- name: number
dtype: int64
- name: title
dtype: string
- name: user
struct:
- name: login
dtype: string
- name: id
dtype: int64
- name: node_id
dtype: string
- name: avatar_url
dtype: string
- name: gravatar_id
dtype: string
- name: url
dtype: string
- name: html_url
dtype: string
- name: followers_url
dtype: string
- name: following_url
dtype: string
- name: gists_url
dtype: string
- name: starred_url
dtype: string
- name: subscriptions_url
dtype: string
- name: organizations_url
dtype: string
- name: repos_url
dtype: string
- name: events_url
dtype: string
- name: received_events_url
dtype: string
- name: type
dtype: string
- name: site_admin
dtype: bool
- name: labels
list:
- name: id
dtype: int64
- name: node_id
dtype: string
- name: url
dtype: string
- name: name
dtype: string
- name: color
dtype: string
- name: default
dtype: bool
- name: description
dtype: string
- name: state
dtype: string
- name: locked
dtype: bool
- name: assignee
struct:
- name: login
dtype: string
- name: id
dtype: int64
- name: node_id
dtype: string
- name: avatar_url
dtype: string
- name: gravatar_id
dtype: string
- name: url
dtype: string
- name: html_url
dtype: string
- name: followers_url
dtype: string
- name: following_url
dtype: string
- name: gists_url
dtype: string
- name: starred_url
dtype: string
- name: subscriptions_url
dtype: string
- name: organizations_url
dtype: string
- name: repos_url
dtype: string
- name: events_url
dtype: string
- name: received_events_url
dtype: string
- name: type
dtype: string
- name: site_admin
dtype: bool
- name: assignees
list:
- name: login
dtype: string
- name: id
dtype: int64
- name: node_id
dtype: string
- name: avatar_url
dtype: string
- name: gravatar_id
dtype: string
- name: url
dtype: string
- name: html_url
dtype: string
- name: followers_url
dtype: string
- name: following_url
dtype: string
- name: gists_url
dtype: string
- name: starred_url
dtype: string
- name: subscriptions_url
dtype: string
- name: organizations_url
dtype: string
- name: repos_url
dtype: string
- name: events_url
dtype: string
- name: received_events_url
dtype: string
- name: type
dtype: string
- name: site_admin
dtype: bool
- name: comments
sequence: string
- name: created_at
dtype: timestamp[s]
- name: updated_at
dtype: timestamp[s]
- name: closed_at
dtype: timestamp[s]
- name: author_association
dtype: string
- name: active_lock_reason
dtype: 'null'
- name: draft
dtype: bool
- name: pull_request
struct:
- name: url
dtype: string
- name: html_url
dtype: string
- name: diff_url
dtype: string
- name: patch_url
dtype: string
- name: merged_at
dtype: timestamp[s]
- name: body
dtype: string
- name: reactions
struct:
- name: url
dtype: string
- name: total_count
dtype: int64
- name: '+1'
dtype: int64
- name: '-1'
dtype: int64
- name: laugh
dtype: int64
- name: hooray
dtype: int64
- name: confused
dtype: int64
- name: heart
dtype: int64
- name: rocket
dtype: int64
- name: eyes
dtype: int64
- name: timeline_url
dtype: string
- name: performed_via_github_app
dtype: 'null'
- name: state_reason
dtype: string
- name: is_pull_request
dtype: bool
splits:
- name: train
num_bytes: 32588261
num_examples: 6480
download_size: 9171683
dataset_size: 32588261
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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hf-vision/hardhat | hf-vision | 2023-12-17T18:29:06Z | 4 | 0 | [
"region:us"
] | null | 2023-12-17T17:18:12Z | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: image
dtype: image
- name: image_id
dtype: int64
- name: width
dtype: int64
- name: height
dtype: int64
- name: objects
struct:
- name: id
sequence: int64
- name: area
sequence: float64
- name: bbox
sequence:
sequence: float64
- name: category
sequence: string
splits:
- name: train
num_bytes: 207310502.085
num_examples: 5297
- name: test
num_bytes: 67741175.806
num_examples: 1766
download_size: 266886357
dataset_size: 275051677.89100003
---
# Dataset Card for "hardhat"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Aashi/All_About_Apple_Devices | Aashi | 2023-12-18T00:11:15Z | 4 | 2 | [
"task_categories:question-answering",
"task_categories:conversational",
"size_categories:n<1K",
"language:en",
"license:mit",
"tech",
"region:us"
] | [
"question-answering",
"conversational"
] | 2023-12-17T23:51:57Z | ---
license: mit
task_categories:
- question-answering
- conversational
language:
- en
tags:
- tech
pretty_name: A3D 🚀
size_categories:
- n<1K
---
This dataset contains Q&A based on what kind of questions do people ask online with their respective answers. This can be used as an LLM project where we finetune an LLM and create a chatbot where one can ask the chatbot any question related to Apple products and get respective answers. | [
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openclimatefix/eumetsat-rss | openclimatefix | 2023-12-15T10:43:36Z | 3 | 1 | [
"size_categories:1K<n<10K",
"license:other",
"climate",
"doi:10.57967/hf/1488",
"region:us"
] | null | 2022-09-05T09:25:53Z | ---
license: other
tags:
- climate
size_categories:
- 1K<n<10K
---
NOTE: All this data, plus a lot more, is now accessible at https://console.cloud.google.com/marketplace/product/bigquery-public-data/eumetsat-seviri-rss-hrv-uk?project=tactile-acrobat-249716
That dataset is the preferred way to access this data, as it goes back to the beginning of the RSS archive (2008-2023) and is updated on a roughly weekly basis.
This dataset consists of the EUMETSAT Rapid Scan Service (RSS) imagery for 2014 to Feb 2023. This data has 2 formats, the High Resolution Visible channel (HRV) which covers Europe and North Africa at a resolution of roughly 2-3km per pixel, and is shifted each day to better image where the sun is shining, and the non-HRV data, which is comprised of 11 spectral channels at a 6-9km resolution covering the top third of the Earth centered on Europe. These images are taken 5 minutes apart and have been compressed and stacked into Zarr stores. Using Xarray, these files can be opened all together to create one large Zarr store of HRV or non-HRV imagery. | [
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openclimatefix/dwd-icon-eu | openclimatefix | 2023-12-17T22:11:46Z | 3 | 3 | [
"size_categories:1K<n<10K",
"license:mit",
"climate",
"doi:10.57967/hf/0879",
"region:us"
] | null | 2023-03-18T09:42:30Z | ---
license: mit
tags:
- climate
pretty_name: DWD ICON-EU Forecasts
size_categories:
- 1K<n<10K
---
# Dataset Card for DWD ICON-EU Forecast
This dataset is comprised of forecasts from the German Weather Service's (DWD) ICON-EU model. From 2020-March 2023 the forecasts contain variables that are relevant to solar and wind
forecasting. From March 2023 to the present, all variables are included. Each forecast runs up to 5 days into the future, and the model is ran 4 times per day. This data is an archive of
the publicly available data at https://opendata.dwd.de/weather/nwp/, converted to Zarr format with Xarray. No other processing of the data is performed.
## Dataset Details
- **Curated by:** Jacob Bieker, Open Climate Fix
- **License:** German Government Open Data License
### Dataset Sources [optional]
- **Raw files:** https://opendata.dwd.de/weather/nwp/
Note: The raw files are deleted after 24 hours, and there is no long-term archive available publicly.
## Uses
This data is intended for use in renewable energy forecasting, weather forecasting, and anything that can use high-quality weather forecasts over Europe.
## Dataset Structure
The dataset is comprised of one Zarr file per forecast initialization time, and each forecast goes out between 48-120 hours. The files are located at data/year/month/day/YYYYMMDDHH.zarr.zip.
## Dataset Creation
### Curation Rationale
The DWD ICON-EU model provides high-quality, high-resolution forecasts for European weather that is also publicly available and free of charge. The model should generally outperform
NOAA's GFS forecast model, and has a higher temporal and spatial resolution. The main downside of this model is that the files are only available for a short period publicly, so this dataset
was setup to provide a public archive of the forecasts for use by researchers in many fields, but especially renewable energy forecasting and weather forecasting.
### Source Data
The source data is the grib2 files from the DWD Open Data Server.
#### Data Collection and Processing
The data is collected every day, around 6-8 hours after forecast initialization time to ensure the forecast is finished running before the data is pulled. The grib2 files are opened
with Xarray and collated into a single Xarray Dataset, with one data variable per ICON variable. Surface variables have "_s" appended to their names to differentiate them from multi-level variables.
The Dataset is then written to Zarr using "ocf_blosc2" to encode and compress the variables. No scaling or changing of the variables values is performed.
#### Who are the source data producers?
German Weather Service (DWD)
### Recommendations
These files can be opened directly from HuggingFace, and streamed in with Xarray. HuggingFace is fairly slow though, so the recommended way would be to download the files you want
and open them locally. In either case, to access the data you can do the following
```python
import ocf_blosc2
import xarray as xr
data = xr.open_zarr("path/to/zarr/file")
print(data)
```
Alternatively, for using the data in forecasting, there is the `ocf_datapipes` package for loading and training renewable energy forecasting models with multi-modal inputs, including
ICON, but also satellite data, PV readings, etc.
## Dataset Card Contact
Jacob Bieker: [email protected] | [
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] |
hayden-donnelly/world-heightmaps-01 | hayden-donnelly | 2023-12-12T23:56:47Z | 3 | 1 | [
"task_categories:unconditional-image-generation",
"task_categories:image-classification",
"task_categories:text-to-image",
"size_categories:100K<n<1M",
"license:apache-2.0",
"region:us"
] | [
"unconditional-image-generation",
"image-classification",
"text-to-image"
] | 2023-07-15T23:43:09Z | ---
license: apache-2.0
task_categories:
- unconditional-image-generation
- image-classification
- text-to-image
pretty_name: World Heightmaps 01
viewer: false
size_categories:
- 100K<n<1M
---
# World Heightmaps 01
This is a dataset of ~600k 360x360 heightmaps. The heightmaps are labelled according to their latitude and longitude,
as well as a 1-dimensional slice ID. This slice ID specifies how they were sliced from the overall latitude/longitude image (see below for visualization).
There are a max of 100 such slices for each latitude/longitude, but usually there are fewer because of data cleaning.
<img src="https://i.imgur.com/6gaoxEV.png" width="1000px"></img>
# Directory Structure
Folder name is latitude/longitude, image name is slice ID. Some folders also contain an image called "whole" which is the whole latitude/longitude image scaled down to 360x360.
```
n00_e010/
0.png
1.png
3.png
...
99.png
whole.png
n00_e011/
0.png
1.png
2.png
...
99.png
whole.png
...
``` | [
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ganeshjcs/hindi-article-summarization | ganeshjcs | 2023-12-14T16:10:20Z | 3 | 0 | [
"license:cc-by-sa-4.0",
"region:us"
] | null | 2023-09-14T03:15:29Z | ---
license: cc-by-sa-4.0
---
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rchan26/english_char_split | rchan26 | 2023-12-11T18:15:18Z | 3 | 0 | [
"region:us"
] | null | 2023-10-10T22:40:35Z | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: word
dtype: string
- name: language
dtype: string
- name: input_ids
sequence: int32
- name: attention_mask
sequence: int8
- name: special_tokens_mask
sequence: int8
- name: tokens
sequence: string
splits:
- name: train
num_bytes: 5310458
num_examples: 37849
- name: test
num_bytes: 1981786
num_examples: 14123
- name: validation
num_bytes: 2614514
num_examples: 18643
download_size: 2205128
dataset_size: 9906758
---
# Dataset Card for "english_char_split"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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sabman/llmrouter | sabman | 2023-12-15T07:19:54Z | 3 | 1 | [
"license:cc-by-4.0",
"region:us"
] | null | 2023-10-26T16:44:40Z | ---
license: cc-by-4.0
---
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taesiri/arxiv_db | taesiri | 2023-12-18T01:19:40Z | 3 | 2 | [
"license:cc-by-nc-4.0",
"region:us"
] | null | 2023-10-26T23:53:25Z | ---
license: cc-by-nc-4.0
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harpreetsahota/three_shot_comparison | harpreetsahota | 2023-12-11T16:31:14Z | 3 | 0 | [
"region:us"
] | null | 2023-11-15T15:09:19Z | ---
dataset_info:
features:
- name: source
dtype: string
- name: target
dtype: string
- name: rationale
dtype: string
- name: task
dtype: string
- name: type
dtype: string
- name: decilm_generation
dtype: string
- name: mistral_generation
dtype: string
splits:
- name: train
num_bytes: 66884
num_examples: 30
download_size: 52879
dataset_size: 66884
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "three_shot_comparison"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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open-llm-leaderboard/details_l3utterfly__mistral-7b-v0.1-layla-v2 | open-llm-leaderboard | 2023-12-16T17:47:23Z | 3 | 0 | [
"region:us"
] | null | 2023-11-20T09:07:04Z | ---
pretty_name: Evaluation run of l3utterfly/mistral-7b-v0.1-layla-v2
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [l3utterfly/mistral-7b-v0.1-layla-v2](https://huggingface.co/l3utterfly/mistral-7b-v0.1-layla-v2)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 64 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the aggregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_l3utterfly__mistral-7b-v0.1-layla-v2\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-12-16T17:43:48.335083](https://huggingface.co/datasets/open-llm-leaderboard/details_l3utterfly__mistral-7b-v0.1-layla-v2/blob/main/results_2023-12-16T17-43-48.335083.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.5109909692126704,\n\
\ \"acc_stderr\": 0.034097544063625904,\n \"acc_norm\": 0.5139816809039905,\n\
\ \"acc_norm_stderr\": 0.03481633806243026,\n \"mc1\": 0.3561811505507956,\n\
\ \"mc1_stderr\": 0.01676379072844634,\n \"mc2\": 0.5156921467880321,\n\
\ \"mc2_stderr\": 0.015196148225186935\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.5332764505119454,\n \"acc_stderr\": 0.014578995859605813,\n\
\ \"acc_norm\": 0.5631399317406144,\n \"acc_norm_stderr\": 0.014494421584256515\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6014738099980084,\n\
\ \"acc_stderr\": 0.004885942040894562,\n \"acc_norm\": 0.7976498705437164,\n\
\ \"acc_norm_stderr\": 0.004009307895677153\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \
\ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.48148148148148145,\n\
\ \"acc_stderr\": 0.043163785995113245,\n \"acc_norm\": 0.48148148148148145,\n\
\ \"acc_norm_stderr\": 0.043163785995113245\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.5460526315789473,\n \"acc_stderr\": 0.04051646342874143,\n\
\ \"acc_norm\": 0.5460526315789473,\n \"acc_norm_stderr\": 0.04051646342874143\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.48,\n\
\ \"acc_stderr\": 0.050211673156867795,\n \"acc_norm\": 0.48,\n \
\ \"acc_norm_stderr\": 0.050211673156867795\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.5509433962264151,\n \"acc_stderr\": 0.030612730713641095,\n\
\ \"acc_norm\": 0.5509433962264151,\n \"acc_norm_stderr\": 0.030612730713641095\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.6111111111111112,\n\
\ \"acc_stderr\": 0.04076663253918567,\n \"acc_norm\": 0.6111111111111112,\n\
\ \"acc_norm_stderr\": 0.04076663253918567\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \
\ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\
acc\": 0.4,\n \"acc_stderr\": 0.049236596391733084,\n \"acc_norm\"\
: 0.4,\n \"acc_norm_stderr\": 0.049236596391733084\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.35,\n \"acc_stderr\": 0.047937248544110196,\n \
\ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.047937248544110196\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.4913294797687861,\n\
\ \"acc_stderr\": 0.038118909889404126,\n \"acc_norm\": 0.4913294797687861,\n\
\ \"acc_norm_stderr\": 0.038118909889404126\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.24509803921568626,\n \"acc_stderr\": 0.042801058373643966,\n\
\ \"acc_norm\": 0.24509803921568626,\n \"acc_norm_stderr\": 0.042801058373643966\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.62,\n \"acc_stderr\": 0.048783173121456316,\n \"acc_norm\": 0.62,\n\
\ \"acc_norm_stderr\": 0.048783173121456316\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.4765957446808511,\n \"acc_stderr\": 0.032650194750335815,\n\
\ \"acc_norm\": 0.4765957446808511,\n \"acc_norm_stderr\": 0.032650194750335815\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.3508771929824561,\n\
\ \"acc_stderr\": 0.044895393502706986,\n \"acc_norm\": 0.3508771929824561,\n\
\ \"acc_norm_stderr\": 0.044895393502706986\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.46206896551724136,\n \"acc_stderr\": 0.04154659671707548,\n\
\ \"acc_norm\": 0.46206896551724136,\n \"acc_norm_stderr\": 0.04154659671707548\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.3148148148148148,\n \"acc_stderr\": 0.02391998416404772,\n \"\
acc_norm\": 0.3148148148148148,\n \"acc_norm_stderr\": 0.02391998416404772\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.30952380952380953,\n\
\ \"acc_stderr\": 0.04134913018303316,\n \"acc_norm\": 0.30952380952380953,\n\
\ \"acc_norm_stderr\": 0.04134913018303316\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.24,\n \"acc_stderr\": 0.042923469599092816,\n \
\ \"acc_norm\": 0.24,\n \"acc_norm_stderr\": 0.042923469599092816\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\
: 0.603225806451613,\n \"acc_stderr\": 0.027831231605767944,\n \"\
acc_norm\": 0.603225806451613,\n \"acc_norm_stderr\": 0.027831231605767944\n\
\ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\
: 0.37438423645320196,\n \"acc_stderr\": 0.03405155380561952,\n \"\
acc_norm\": 0.37438423645320196,\n \"acc_norm_stderr\": 0.03405155380561952\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.52,\n \"acc_stderr\": 0.050211673156867795,\n \"acc_norm\"\
: 0.52,\n \"acc_norm_stderr\": 0.050211673156867795\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.6303030303030303,\n \"acc_stderr\": 0.03769430314512568,\n\
\ \"acc_norm\": 0.6303030303030303,\n \"acc_norm_stderr\": 0.03769430314512568\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.6111111111111112,\n \"acc_stderr\": 0.0347327959083696,\n \"acc_norm\"\
: 0.6111111111111112,\n \"acc_norm_stderr\": 0.0347327959083696\n },\n\
\ \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n \
\ \"acc\": 0.7253886010362695,\n \"acc_stderr\": 0.03221024508041153,\n\
\ \"acc_norm\": 0.7253886010362695,\n \"acc_norm_stderr\": 0.03221024508041153\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.4512820512820513,\n \"acc_stderr\": 0.025230381238934837,\n\
\ \"acc_norm\": 0.4512820512820513,\n \"acc_norm_stderr\": 0.025230381238934837\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.26296296296296295,\n \"acc_stderr\": 0.02684205787383371,\n \
\ \"acc_norm\": 0.26296296296296295,\n \"acc_norm_stderr\": 0.02684205787383371\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.46638655462184875,\n \"acc_stderr\": 0.03240501447690071,\n\
\ \"acc_norm\": 0.46638655462184875,\n \"acc_norm_stderr\": 0.03240501447690071\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.26490066225165565,\n \"acc_stderr\": 0.03603038545360384,\n \"\
acc_norm\": 0.26490066225165565,\n \"acc_norm_stderr\": 0.03603038545360384\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.6807339449541284,\n \"acc_stderr\": 0.019987829069750027,\n \"\
acc_norm\": 0.6807339449541284,\n \"acc_norm_stderr\": 0.019987829069750027\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.28703703703703703,\n \"acc_stderr\": 0.030851992993257013,\n \"\
acc_norm\": 0.28703703703703703,\n \"acc_norm_stderr\": 0.030851992993257013\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.6568627450980392,\n \"acc_stderr\": 0.033321399446680854,\n \"\
acc_norm\": 0.6568627450980392,\n \"acc_norm_stderr\": 0.033321399446680854\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.6455696202531646,\n \"acc_stderr\": 0.0311373042971858,\n \
\ \"acc_norm\": 0.6455696202531646,\n \"acc_norm_stderr\": 0.0311373042971858\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6143497757847534,\n\
\ \"acc_stderr\": 0.03266842214289201,\n \"acc_norm\": 0.6143497757847534,\n\
\ \"acc_norm_stderr\": 0.03266842214289201\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.5725190839694656,\n \"acc_stderr\": 0.04338920305792401,\n\
\ \"acc_norm\": 0.5725190839694656,\n \"acc_norm_stderr\": 0.04338920305792401\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.6859504132231405,\n \"acc_stderr\": 0.042369647530410184,\n \"\
acc_norm\": 0.6859504132231405,\n \"acc_norm_stderr\": 0.042369647530410184\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.5185185185185185,\n\
\ \"acc_stderr\": 0.04830366024635331,\n \"acc_norm\": 0.5185185185185185,\n\
\ \"acc_norm_stderr\": 0.04830366024635331\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.6012269938650306,\n \"acc_stderr\": 0.03847021420456023,\n\
\ \"acc_norm\": 0.6012269938650306,\n \"acc_norm_stderr\": 0.03847021420456023\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.4107142857142857,\n\
\ \"acc_stderr\": 0.046695106638751906,\n \"acc_norm\": 0.4107142857142857,\n\
\ \"acc_norm_stderr\": 0.046695106638751906\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.6699029126213593,\n \"acc_stderr\": 0.0465614711001235,\n\
\ \"acc_norm\": 0.6699029126213593,\n \"acc_norm_stderr\": 0.0465614711001235\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.7692307692307693,\n\
\ \"acc_stderr\": 0.02760192138141762,\n \"acc_norm\": 0.7692307692307693,\n\
\ \"acc_norm_stderr\": 0.02760192138141762\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.64,\n \"acc_stderr\": 0.04824181513244218,\n \
\ \"acc_norm\": 0.64,\n \"acc_norm_stderr\": 0.04824181513244218\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.7241379310344828,\n\
\ \"acc_stderr\": 0.01598281477469563,\n \"acc_norm\": 0.7241379310344828,\n\
\ \"acc_norm_stderr\": 0.01598281477469563\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.5173410404624278,\n \"acc_stderr\": 0.02690290045866664,\n\
\ \"acc_norm\": 0.5173410404624278,\n \"acc_norm_stderr\": 0.02690290045866664\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.33743016759776534,\n\
\ \"acc_stderr\": 0.01581390128391305,\n \"acc_norm\": 0.33743016759776534,\n\
\ \"acc_norm_stderr\": 0.01581390128391305\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.5130718954248366,\n \"acc_stderr\": 0.028620130800700246,\n\
\ \"acc_norm\": 0.5130718954248366,\n \"acc_norm_stderr\": 0.028620130800700246\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.5562700964630225,\n\
\ \"acc_stderr\": 0.02821768355665231,\n \"acc_norm\": 0.5562700964630225,\n\
\ \"acc_norm_stderr\": 0.02821768355665231\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.5493827160493827,\n \"acc_stderr\": 0.027684721415656203,\n\
\ \"acc_norm\": 0.5493827160493827,\n \"acc_norm_stderr\": 0.027684721415656203\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.3191489361702128,\n \"acc_stderr\": 0.027807990141320196,\n \
\ \"acc_norm\": 0.3191489361702128,\n \"acc_norm_stderr\": 0.027807990141320196\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.3650586701434159,\n\
\ \"acc_stderr\": 0.012296373743443478,\n \"acc_norm\": 0.3650586701434159,\n\
\ \"acc_norm_stderr\": 0.012296373743443478\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.4742647058823529,\n \"acc_stderr\": 0.03033257809455504,\n\
\ \"acc_norm\": 0.4742647058823529,\n \"acc_norm_stderr\": 0.03033257809455504\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.5196078431372549,\n \"acc_stderr\": 0.020212274976302957,\n \
\ \"acc_norm\": 0.5196078431372549,\n \"acc_norm_stderr\": 0.020212274976302957\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6181818181818182,\n\
\ \"acc_stderr\": 0.046534298079135075,\n \"acc_norm\": 0.6181818181818182,\n\
\ \"acc_norm_stderr\": 0.046534298079135075\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.5510204081632653,\n \"acc_stderr\": 0.03184213866687579,\n\
\ \"acc_norm\": 0.5510204081632653,\n \"acc_norm_stderr\": 0.03184213866687579\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.7661691542288557,\n\
\ \"acc_stderr\": 0.029929415408348387,\n \"acc_norm\": 0.7661691542288557,\n\
\ \"acc_norm_stderr\": 0.029929415408348387\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.73,\n \"acc_stderr\": 0.0446196043338474,\n \
\ \"acc_norm\": 0.73,\n \"acc_norm_stderr\": 0.0446196043338474\n },\n\
\ \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5120481927710844,\n\
\ \"acc_stderr\": 0.03891364495835817,\n \"acc_norm\": 0.5120481927710844,\n\
\ \"acc_norm_stderr\": 0.03891364495835817\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.7485380116959064,\n \"acc_stderr\": 0.033275044238468436,\n\
\ \"acc_norm\": 0.7485380116959064,\n \"acc_norm_stderr\": 0.033275044238468436\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.3561811505507956,\n\
\ \"mc1_stderr\": 0.01676379072844634,\n \"mc2\": 0.5156921467880321,\n\
\ \"mc2_stderr\": 0.015196148225186935\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7576953433307024,\n \"acc_stderr\": 0.012042352526174789\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.31387414708112205,\n \
\ \"acc_stderr\": 0.01278268125105321\n }\n}\n```"
repo_url: https://huggingface.co/l3utterfly/mistral-7b-v0.1-layla-v2
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: [email protected]
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|arc:challenge|25_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|arc:challenge|25_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|drop|3_2023-11-20T09-04-01.597218.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-11-20T09-04-01.597218.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|gsm8k|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|gsm8k|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hellaswag|10_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hellaswag|10_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-11-20T09-04-01.597218.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-16T17-43-48.335083.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-management|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-virology|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|truthfulqa:mc|0_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-16T17-43-48.335083.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- '**/details_harness|winogrande|5_2023-11-20T09-04-01.597218.parquet'
- split: 2023_12_16T17_43_48.335083
path:
- '**/details_harness|winogrande|5_2023-12-16T17-43-48.335083.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-12-16T17-43-48.335083.parquet'
- config_name: results
data_files:
- split: 2023_11_20T09_04_01.597218
path:
- results_2023-11-20T09-04-01.597218.parquet
- split: 2023_12_16T17_43_48.335083
path:
- results_2023-12-16T17-43-48.335083.parquet
- split: latest
path:
- results_2023-12-16T17-43-48.335083.parquet
---
# Dataset Card for Evaluation run of l3utterfly/mistral-7b-v0.1-layla-v2
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [l3utterfly/mistral-7b-v0.1-layla-v2](https://huggingface.co/l3utterfly/mistral-7b-v0.1-layla-v2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_l3utterfly__mistral-7b-v0.1-layla-v2",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-12-16T17:43:48.335083](https://huggingface.co/datasets/open-llm-leaderboard/details_l3utterfly__mistral-7b-v0.1-layla-v2/blob/main/results_2023-12-16T17-43-48.335083.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"acc": 0.5109909692126704,
"acc_stderr": 0.034097544063625904,
"acc_norm": 0.5139816809039905,
"acc_norm_stderr": 0.03481633806243026,
"mc1": 0.3561811505507956,
"mc1_stderr": 0.01676379072844634,
"mc2": 0.5156921467880321,
"mc2_stderr": 0.015196148225186935
},
"harness|arc:challenge|25": {
"acc": 0.5332764505119454,
"acc_stderr": 0.014578995859605813,
"acc_norm": 0.5631399317406144,
"acc_norm_stderr": 0.014494421584256515
},
"harness|hellaswag|10": {
"acc": 0.6014738099980084,
"acc_stderr": 0.004885942040894562,
"acc_norm": 0.7976498705437164,
"acc_norm_stderr": 0.004009307895677153
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.25,
"acc_stderr": 0.04351941398892446,
"acc_norm": 0.25,
"acc_norm_stderr": 0.04351941398892446
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.48148148148148145,
"acc_stderr": 0.043163785995113245,
"acc_norm": 0.48148148148148145,
"acc_norm_stderr": 0.043163785995113245
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.5460526315789473,
"acc_stderr": 0.04051646342874143,
"acc_norm": 0.5460526315789473,
"acc_norm_stderr": 0.04051646342874143
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.48,
"acc_stderr": 0.050211673156867795,
"acc_norm": 0.48,
"acc_norm_stderr": 0.050211673156867795
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.5509433962264151,
"acc_stderr": 0.030612730713641095,
"acc_norm": 0.5509433962264151,
"acc_norm_stderr": 0.030612730713641095
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.6111111111111112,
"acc_stderr": 0.04076663253918567,
"acc_norm": 0.6111111111111112,
"acc_norm_stderr": 0.04076663253918567
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.32,
"acc_stderr": 0.046882617226215034,
"acc_norm": 0.32,
"acc_norm_stderr": 0.046882617226215034
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.4,
"acc_stderr": 0.049236596391733084,
"acc_norm": 0.4,
"acc_norm_stderr": 0.049236596391733084
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.35,
"acc_stderr": 0.047937248544110196,
"acc_norm": 0.35,
"acc_norm_stderr": 0.047937248544110196
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.4913294797687861,
"acc_stderr": 0.038118909889404126,
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```
## Dataset Details
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[More Information Needed] | [
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Pipp/SplatTest | Pipp | 2023-12-12T19:40:11Z | 3 | 0 | [
"license:mit",
"region:us"
] | null | 2023-11-24T23:30:55Z | ---
license: mit
---
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worldboss/bank-of-ghana-treasury-bills | worldboss | 2023-12-15T05:47:16Z | 3 | 0 | [
"task_categories:conversational",
"task_categories:text-generation",
"task_categories:summarization",
"task_categories:question-answering",
"task_categories:text-classification",
"task_categories:text-retrieval",
"task_categories:translation",
"size_categories:10K<n<100K",
"language:en",
"license:apache-2.0",
"ghana",
"news",
"ghana-news",
"bank-of-ghana",
"exchange-rates",
"ghana data",
"bank of ghana",
"region:us"
] | [
"conversational",
"text-generation",
"summarization",
"question-answering",
"text-classification",
"text-retrieval",
"translation"
] | 2023-11-25T01:23:08Z | ---
language:
- en
license: apache-2.0
size_categories:
- 10K<n<100K
task_categories:
- conversational
- text-generation
- summarization
- question-answering
- text-classification
- text-retrieval
- translation
pretty_name: No Robots
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: Issue_Date
dtype: string
- name: Tender
dtype: int64
- name: Security_Type
dtype: string
- name: Discount_Rate
dtype: float64
- name: Interest_Rate
dtype: float64
splits:
- name: train
num_bytes: 49712
num_examples: 946
download_size: 23368
dataset_size: 49712
tags:
- ghana
- news
- ghana-news
- bank-of-ghana
- exchange-rates
- ghana data
- bank of ghana
---
### Description 🙅♂️🤖
Bank of Ghana historical and real-time treasury bills data. [Bank of Ghana](https://www.bog.gov.gh/treasury-and-the-markets/treasury-bill-rates/)
Click Here: [](https://colab.research.google.com/drive/1zZUIyp9zBhwL5CqHS3Ggf5vJCr_yTYw0?usp=sharing)
### Data Format
```shell
{
"issue_date": "...",
"tender": "...",
"security_type": "...",
"discount_rate": "...",
"interest_rate": "..."
}
```
### Load Dataset
```shell
pip install datasets
```
```python
from datasets import load_dataset
treasury = load_dataset("worldboss/bank-of-ghana-treasury-bills", split="train")
pd.DataFrame(treasury).head()
```
### Author
The data was constructed by Theophilus Siameh ([email protected]). | [
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argilla/end2end_textclassification_with_vectors | argilla | 2023-12-15T16:53:40Z | 3 | 0 | [
"size_categories:1K<n<10K",
"rlfh",
"argilla",
"human-feedback",
"region:us"
] | null | 2023-11-29T14:38:40Z | ---
size_categories: 1K<n<10K
tags:
- rlfh
- argilla
- human-feedback
---
# Dataset Card for end2end_textclassification_with_vectors
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("argilla/end2end_textclassification_with_vectors")
```
### 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("argilla/end2end_textclassification_with_vectors")
```
### Supported Tasks and Leaderboards
This dataset can contain [multiple fields, questions and responses](https://docs.argilla.io/en/latest/conceptual_guides/data_model.html#feedback-dataset) 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**, **metadata**, **vectors**, and **guidelines**.
The **fields** are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.
| Field Name | Title | Type | Required | Markdown |
| ---------- | ----- | ---- | -------- | -------- |
| text | Text | FieldTypes.text | True | False |
The **questions** are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label_selection, multi_label_selection, or ranking.
| Question Name | Title | Type | Required | Description | Values/Labels |
| ------------- | ----- | ---- | -------- | ----------- | ------------- |
| label | Label | QuestionTypes.label_selection | True | N/A | ['World', 'Sports', 'Business', 'Sci/Tech'] |
The **suggestions** are human or machine generated recommendations for each question to assist the annotator during the annotation process, so those are always linked to the existing questions, and 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, but the column name is appended with "-suggestion" and the metadata is appended with "-suggestion-metadata".
The **metadata** is a dictionary that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the `metadata_properties` defined in the dataset configuration file in `argilla.yaml`.
**✨ NEW** The **vectors** are different columns that contain a vector in floating point, which is constraint to the pre-defined dimensions in the **vectors_settings** when configuring the vectors within the dataset itself, also the dimensions will always be 1-dimensional. The **vectors** are optional and identified by the pre-defined vector name in the dataset configuration file in `argilla.yaml`.
| Vector Name | Title | Dimensions |
|-------------|-------|------------|
| sentence_embedding | Sentence Embedding | [1, 384] |
| Metadata Name | Title | Type | Values | Visible for Annotators |
| ------------- | ----- | ---- | ------ | ---------------------- |
The **guidelines**, are optional as well, and 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
{
"external_id": "record-0",
"fields": {
"text": "Wall St. Bears Claw Back Into the Black (Reuters) Reuters - Short-sellers, Wall Street\u0027s dwindling\\band of ultra-cynics, are seeing green again."
},
"metadata": {},
"responses": [],
"suggestions": [],
"vectors": {
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}
}
```
While the same record in HuggingFace `datasets` looks as follows:
```json
{
"external_id": "record-0",
"label": [],
"label-suggestion": null,
"label-suggestion-metadata": {
"agent": null,
"score": null,
"type": null
},
"metadata": "{}",
"text": "Wall St. Bears Claw Back Into the Black (Reuters) Reuters - Short-sellers, Wall Street\u0027s dwindling\\band of ultra-cynics, are seeing green again.",
"vectors": {
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}
}
```
### 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 supported. These are the ones that will be used to provide responses to the questions.
* **text** is of type `FieldTypes.text`.
* **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`.
* **label** is of type `QuestionTypes.label_selection` with the following allowed values ['World', 'Sports', 'Business', 'Sci/Tech'].
* **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) **label-suggestion** is of type `QuestionTypes.label_selection` with the following allowed values ['World', 'Sports', 'Business', 'Sci/Tech'].
* **✨ NEW** **Vectors**: As of Argilla 1.19.0, the vectors have been included in order to add support for similarity search to explore similar records based on vector search powered by the search engine defined. The vectors are optional and cannot be seen within the UI, those are uploaded and internally used. Also the vectors will always be optional, and only the dimensions previously defined in their settings.
* (optional) **sentence_embedding** is of type `float32` and has a dimension of (1, `384`).
Additionally, we also have two more fields that are optional and are the following:
* **metadata:** This is an optional field that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the `metadata_properties` defined in the dataset configuration file in `argilla.yaml`.
* **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
Classify the articles into one of the four categories.
#### 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] | [
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Adarshtiwari144/llama_finetunig | Adarshtiwari144 | 2023-12-13T19:36:33Z | 3 | 0 | [
"license:mit",
"region:us"
] | null | 2023-12-01T16:23:58Z | ---
license: mit
---
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chathuru/cicids2018 | chathuru | 2023-12-17T14:51:56Z | 3 | 0 | [
"task_categories:text-classification",
"Cybersecurity",
"Network Intrusion Detection",
"CIC-IDS2018",
"region:us"
] | [
"text-classification"
] | 2023-12-02T13:47:26Z | ---
task_categories:
- text-classification
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 31093
num_examples: 96
- name: test
num_bytes: 7562
num_examples: 24
download_size: 21577
dataset_size: 38655
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
tags:
- Cybersecurity
- Network Intrusion Detection
- CIC-IDS2018
---
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jahb57/gpt2_embeddings_BATCH_14 | jahb57 | 2023-12-11T15:21:03Z | 3 | 0 | [
"region:us"
] | null | 2023-12-04T02:46:14Z | ---
dataset_info:
features:
- name: sentence
dtype: string
- name: last_hidden_state
sequence:
sequence: float32
splits:
- name: train
num_bytes: 18580842836
num_examples: 100000
download_size: 18629530835
dataset_size: 18580842836
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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ademax/ocr_redseal_vi | ademax | 2023-12-11T03:42:11Z | 3 | 0 | [
"region:us"
] | null | 2023-12-11T03:35:50Z | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
- name: Noise_level
dtype: int64
- name: meta
struct:
- name: path
dtype: string
- name: subset
dtype: string
- name: path
dtype: 'null'
splits:
- name: train
num_bytes: 5525894060.375
num_examples: 558181
download_size: 5529921734
dataset_size: 5525894060.375
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "ocr_redseal_vi"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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ademax/ocr_sohieu_vi | ademax | 2023-12-11T03:49:02Z | 3 | 0 | [
"region:us"
] | null | 2023-12-11T03:48:57Z | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
- name: meta
struct:
- name: path
dtype: string
- name: subset
dtype: string
- name: path
dtype: 'null'
splits:
- name: train
num_bytes: 4268072.0
num_examples: 644
download_size: 4266549
dataset_size: 4268072.0
---
# Dataset Card for "ocr_sohieu_vi"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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] |
ademax/ocr_uppercase_vi | ademax | 2023-12-11T03:51:47Z | 3 | 0 | [
"region:us"
] | null | 2023-12-11T03:51:13Z | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
- name: meta
struct:
- name: path
dtype: string
- name: subset
dtype: string
- name: path
dtype: 'null'
splits:
- name: train
num_bytes: 499271753.625
num_examples: 12323
download_size: 499066965
dataset_size: 499271753.625
---
# Dataset Card for "ocr_uppercase_vi"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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ademax/ocr_fontsEnhance_vi | ademax | 2023-12-11T04:09:32Z | 3 | 0 | [
"region:us"
] | null | 2023-12-11T04:06:21Z | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
- name: meta
struct:
- name: path
dtype: string
- name: subset
dtype: string
- name: path
dtype: 'null'
splits:
- name: train
num_bytes: 2715797840.875
num_examples: 125753
download_size: 2712543570
dataset_size: 2715797840.875
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "ocr_fontsEnhance_vi"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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ademax/ocr_nameEntityRed_vi | ademax | 2023-12-11T04:15:03Z | 3 | 0 | [
"region:us"
] | null | 2023-12-11T04:14:33Z | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
- name: meta
struct:
- name: path
dtype: string
- name: subset
dtype: string
- name: path
dtype: 'null'
splits:
- name: train
num_bytes: 348986062.5
num_examples: 57500
download_size: 352082024
dataset_size: 348986062.5
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "ocr_nameEntityRed_vi"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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] |
Dusduo/1stGen-Pokemon-Images | Dusduo | 2023-12-17T10:32:22Z | 3 | 0 | [
"region:us"
] | null | 2023-12-11T05:53:35Z | ---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Abra
'1': Aerodactyl
'2': Alakazam
'3': Arbok
'4': Arcanine
'5': Articuno
'6': Beedrill
'7': Bellsprout
'8': Blastoise
'9': Bulbasaur
'10': Butterfree
'11': Caterpie
'12': Chansey
'13': Charizard
'14': Charmander
'15': Charmeleon
'16': Clefable
'17': Clefairy
'18': Cloyster
'19': Cubone
'20': Dewgong
'21': Diglett
'22': Ditto
'23': Dodrio
'24': Doduo
'25': Dragonair
'26': Dragonite
'27': Dratini
'28': Drowzee
'29': Dugtrio
'30': Eevee
'31': Ekans
'32': Electabuzz
'33': Electrode
'34': Exeggcute
'35': Exeggutor
'36': Farfetchd
'37': Fearow
'38': Flareon
'39': Gastly
'40': Gengar
'41': Geodude
'42': Gloom
'43': Golbat
'44': Goldeen
'45': Golduck
'46': Graveler
'47': Grimer
'48': Growlithe
'49': Gyarados
'50': Haunter
'51': Hitmonchan
'52': Hitmonlee
'53': Horsea
'54': Hypno
'55': Ivysaur
'56': Jigglypuff
'57': Jolteon
'58': Jynx
'59': Kabutops
'60': Kadabra
'61': Kakuna
'62': Kangaskhan
'63': Kingler
'64': Koffing
'65': Lapras
'66': Lickitung
'67': Machamp
'68': Machoke
'69': Machop
'70': Magikarp
'71': Magmar
'72': Magnemite
'73': Magneton
'74': Mankey
'75': Marowak
'76': Meowth
'77': Metapod
'78': Mew
'79': Mewtwo
'80': Moltres
'81': Mr. Mime
'82': MrMime
'83': Nidoking
'84': Nidoqueen
'85': Nidorina
'86': Nidorino
'87': Ninetales
'88': Oddish
'89': Omanyte
'90': Omastar
'91': Parasect
'92': Pidgeot
'93': Pidgeotto
'94': Pidgey
'95': Pikachu
'96': Pinsir
'97': Poliwag
'98': Poliwhirl
'99': Poliwrath
'100': Ponyta
'101': Porygon
'102': Primeape
'103': Psyduck
'104': Raichu
'105': Rapidash
'106': Raticate
'107': Rattata
'108': Rhydon
'109': Rhyhorn
'110': Sandshrew
'111': Sandslash
'112': Scyther
'113': Seadra
'114': Seaking
'115': Seel
'116': Shellder
'117': Slowbro
'118': Slowpoke
'119': Snorlax
'120': Spearow
'121': Squirtle
'122': Starmie
'123': Staryu
'124': Tangela
'125': Tauros
'126': Tentacool
'127': Tentacruel
'128': Vaporeon
'129': Venomoth
'130': Venonat
'131': Venusaur
'132': Victreebel
'133': Vileplume
'134': Voltorb
'135': Vulpix
'136': Wartortle
'137': Weedle
'138': Weepinbell
'139': Weezing
'140': Wigglytuff
'141': Zapdos
'142': Zubat
splits:
- name: train
num_bytes: 1594428375.04
num_examples: 8440
- name: test
num_bytes: 366693088.45
num_examples: 2110
download_size: 1928731574
dataset_size: 1961121463.49
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
# First Generation Pokemon images dataset
Based on the Kaggle dataset [Pokemon Images, First Generation(17000 files)](https://www.kaggle.com/datasets/mikoajkolman/pokemon-images-first-generation17000-files).
There are 143 directories for each Pokemon from the first generation except for Nidoran male and female.
Each directory containing from 50 to 200 images from the considered pokemon. | [
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collabteza/sys-human_db3 | collabteza | 2023-12-11T16:34:17Z | 3 | 1 | [
"region:us"
] | null | 2023-12-11T12:04:45Z | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: System Prompt
dtype: string
- name: Human Prompt
dtype: string
- name: Output
dtype: string
splits:
- name: train
num_bytes: 1092224
num_examples: 1354
download_size: 481074
dataset_size: 1092224
---
# Dataset Card for "sys-human_db3"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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krishan-CSE/Davidson_New | krishan-CSE | 2023-12-11T14:41:48Z | 3 | 0 | [
"license:apache-2.0",
"region:us"
] | null | 2023-12-11T14:40:40Z | ---
license: apache-2.0
---
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SpongeBash/bash_images_2 | SpongeBash | 2023-12-11T16:03:43Z | 3 | 0 | [
"region:us"
] | null | 2023-12-11T16:03:41Z | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 146725.0
num_examples: 12
download_size: 148375
dataset_size: 146725.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "bash_images_2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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kpriyanshu256/semeval-task-8-a-mono-v2-test-paraphrase-2 | kpriyanshu256 | 2023-12-11T18:06:39Z | 3 | 0 | [
"region:us"
] | null | 2023-12-11T18:06:38Z | ---
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype: int64
- name: model
dtype: string
- name: source
dtype: string
- name: id
dtype: int64
- name: paraphrase
dtype: string
- name: paraphrase2
dtype: string
splits:
- name: test
num_bytes: 23387836
num_examples: 5000
download_size: 13353734
dataset_size: 23387836
---
# Dataset Card for "semeval-task-8-a-mono-v2-test-paraphrase-2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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NextDayAI/MultipleResponsesChat_labeled_all_engines_20230901_20231211 | NextDayAI | 2023-12-11T21:35:14Z | 3 | 0 | [
"region:us"
] | null | 2023-12-11T21:34:51Z | ---
dataset_info:
features:
- name: prompt
dtype: string
- name: rejected_response
dtype: string
- name: selected_response
dtype: string
splits:
- name: train
num_bytes: 656550102.5138259
num_examples: 207242
- name: valid
num_bytes: 11880134.743087053
num_examples: 3750
- name: test
num_bytes: 11880134.743087053
num_examples: 3750
download_size: 428326686
dataset_size: 680310372.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: valid
path: data/valid-*
- split: test
path: data/test-*
---
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0.044878363609313965,
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] |
NextDayAI/MultipleResponsesChat_unlabeled_all_engines_20230901_20231211 | NextDayAI | 2023-12-11T21:53:48Z | 3 | 0 | [
"region:us"
] | null | 2023-12-11T21:52:52Z | ---
dataset_info:
features:
- name: prompt
dtype: string
- name: rejected_response
dtype: string
- name: selected_response
dtype: string
splits:
- name: train
num_bytes: 1640010653.7197173
num_examples: 523671
- name: valid
num_bytes: 11744091.14014131
num_examples: 3750
- name: test
num_bytes: 11744091.14014131
num_examples: 3750
download_size: 1046865246
dataset_size: 1663498835.9999998
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: valid
path: data/valid-*
- split: test
path: data/test-*
---
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lum-ai/metal-python-ood-climate-explanatations | lum-ai | 2023-12-11T23:22:07Z | 3 | 0 | [
"region:us"
] | null | 2023-12-11T23:22:05Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: chunk_id
dtype: string
- name: text
dtype: string
- name: start_text
dtype: int64
- name: stop_text
dtype: int64
- name: code
dtype: string
- name: start_code
dtype: int64
- name: stop_code
dtype: int64
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 799974
num_examples: 94
download_size: 48110
dataset_size: 799974
---
# Dataset Card for "metal-python-ood-climate-explanatations"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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] |
thanhdath/vietnamese_legal_closed_qa | thanhdath | 2023-12-18T01:12:24Z | 3 | 0 | [
"region:us"
] | null | 2023-12-12T08:21:47Z | ---
dataset_info:
features:
- name: question
dtype: string
- name: selected_contexts
sequence: string
- name: answer
dtype: string
- name: provider
dtype: string
splits:
- name: train
num_bytes: 541616181
num_examples: 95113
download_size: 193079724
dataset_size: 541616181
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Vietnamese Legal Closed QA dataset
The dataset can be used for RAG Chatbot. It contains 160K samples where each sample in the dataset includes a question, K relevant contexts and an answer generated by OpenAI GPT-4.
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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simonveitner/MetaMathQA-40K-Filtered | simonveitner | 2023-12-12T09:47:42Z | 3 | 0 | [
"region:us"
] | null | 2023-12-12T09:38:00Z | ---
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
splits:
- name: train
num_bytes: 10337682
num_examples: 15259
download_size: 4926366
dataset_size: 10337682
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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kristmh/med_vs_high_and_low_priority | kristmh | 2023-12-12T10:35:34Z | 3 | 0 | [
"region:us"
] | null | 2023-12-12T10:34:56Z | ---
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
- split: train
path: data/train-*
- split: validate
path: data/validate-*
dataset_info:
features:
- name: text_clean
dtype: string
- name: labels
dtype: int64
- name: class
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: test
num_bytes: 20511102
num_examples: 28330
- name: train
num_bytes: 163187020
num_examples: 226633
- name: validate
num_bytes: 20144760
num_examples: 28329
download_size: 102592570
dataset_size: 203842882
---
# Dataset Card for "med_vs_high_and_low_priority"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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shyzii/exercise-llama2 | shyzii | 2023-12-12T10:59:59Z | 3 | 0 | [
"region:us"
] | null | 2023-12-12T10:59:00Z | ---
dataset_info:
features:
- name: text
struct:
- name: text
dtype: string
splits:
- name: train
num_bytes: 7925
num_examples: 48
download_size: 3179
dataset_size: 7925
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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jeswinLLM/RANDOM_DATA | jeswinLLM | 2023-12-12T12:39:57Z | 3 | 0 | [
"region:us"
] | null | 2023-12-12T12:39:54Z | ---
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype:
class_label:
names:
'0': cancel_order
'1': change_order
'2': change_shipping_address
'3': check_cancellation_fee
'4': check_invoice
'5': check_payment_methods
'6': check_refund_policy
'7': complaint
'8': contact_customer_service
'9': contact_human_agent
'10': create_account
'11': delete_account
'12': delivery_options
'13': delivery_period
'14': edit_account
'15': get_invoice
'16': get_refund
'17': newsletter_subscription
'18': payment_issue
'19': place_order
'20': recover_password
'21': registration_problems
'22': review
'23': set_up_shipping_address
'24': switch_account
'25': track_order
'26': track_refund
splits:
- name: train
num_bytes: 1582479.0
num_examples: 26872
download_size: 426257
dataset_size: 1582479.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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kwasganguly/lamini | kwasganguly | 2023-12-12T13:23:16Z | 3 | 0 | [
"region:us"
] | null | 2023-12-12T13:23:14Z | ---
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
- name: input_ids
sequence: int32
- name: attention_mask
sequence: int8
- name: labels
sequence: int64
splits:
- name: train
num_bytes: 1846734.3
num_examples: 1260
- name: test
num_bytes: 205192.7
num_examples: 140
download_size: 698609
dataset_size: 2051927.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
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derexHf/MathInstruct2000 | derexHf | 2023-12-12T13:48:04Z | 3 | 0 | [
"region:us"
] | null | 2023-12-12T13:47:59Z | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 120877641
num_examples: 161289
download_size: 60482176
dataset_size: 120877641
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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tyzhu/wikitext-103-raw-v1-sent-permute-9 | tyzhu | 2023-12-12T15:25:20Z | 3 | 0 | [
"region:us"
] | null | 2023-12-12T15:21:40Z | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 5452148058
num_examples: 18013491
- name: validation
num_bytes: 1159288
num_examples: 3760
- name: test
num_bytes: 1305088
num_examples: 4358
download_size: 3160993133
dataset_size: 5454612434
---
# Dataset Card for "wikitext-103-raw-v1-sent-permute-9"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Sunbird/salt-multispeaker-ach | Sunbird | 2023-12-12T22:55:56Z | 3 | 0 | [
"region:us"
] | null | 2023-12-12T22:55:13Z | ---
dataset_info:
features:
- name: ids
dtype: string
- name: texts
dtype: string
- name: audios
sequence: float32
- name: audio_languages
dtype: string
- name: are_studio
dtype: bool
- name: speaker_ids
dtype: string
- name: sample_rates
dtype: int64
splits:
- name: train
num_bytes: 1789772689
num_examples: 4811
- name: dev
num_bytes: 37429616
num_examples: 101
- name: test
num_bytes: 36224375
num_examples: 96
download_size: 872954526
dataset_size: 1863426680
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: dev
path: data/dev-*
- split: test
path: data/test-*
---
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Mariszka/whisper_in_cs | Mariszka | 2023-12-12T23:40:10Z | 3 | 0 | [
"region:us"
] | null | 2023-12-12T23:33:08Z | ---
dataset_info:
features:
- name: input_features
sequence:
sequence: float32
- name: labels
sequence: int64
splits:
- name: train
num_bytes: 21281114736
num_examples: 22155
- name: test
num_bytes: 7409573720
num_examples: 7714
download_size: 4782714641
dataset_size: 28690688456
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
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HowMannyMore/romanurdu-sentiment-dataset-v2 | HowMannyMore | 2023-12-13T09:38:36Z | 3 | 0 | [
"task_categories:text-classification",
"language:ur",
"code",
"region:us"
] | [
"text-classification"
] | 2023-12-13T09:37:35Z | ---
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype: string
splits:
- name: train
num_bytes: 3049454
num_examples: 31395
- name: test
num_bytes: 337012
num_examples: 3400
- name: valid
num_bytes: 327256
num_examples: 3400
download_size: 2431043
dataset_size: 3713722
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: valid
path: data/valid-*
task_categories:
- text-classification
language:
- ur
tags:
- code
---
# Dataset Card for RomanUrdu-Sentiment-Dataset
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
## Dataset Description
### Dataset Summary
The dataset comprises reviews gathered from sources including IMDb, Jazz, and K-Electric, with each review labeled as 'Positive', 'Negative', or 'Neutral' based on its sentiment. This balanced dataset offers a diverse range of sentiment-labeled reviews in Roman Urdu, making it suitable for training and evaluating sentiment analysis models specific to this language. The primary purpose of this dataset is to support the development of roman urdu products by providing a valuable resource for training machine learning models.
However, working with Roman Urdu presents unique challenges, particularly in the context of code-switching between Urdu and Roman script. Researchers and practitioners leveraging this dataset may encounter difficulties related to language processing and sentiment analysis in this code-switched context. Despite these challenges, the Roman Urdu Sentiment Analysis Dataset offers an invaluable opportunity to advance the understanding and application of sentiment analysis within the specific linguistic and cultural context of Roman Urdu.
### Languages
The dataset consists of texts in the Roman Urdu language. Urdu is a language primarily spoken in Pakistan and parts of India. It is one of the 22 officially recognized languages in India and is also widely spoken by the Pakistani diaspora around the world.
The dataset is primarily focused on spoken Roman Urdu, which encompasses a wide range of topics and genres. It is important to note that the dataset's content may vary, covering conversations, speeches, interviews, narratives, and other forms of vocal communication in the Urdu language.
## Dataset Structure
### Data Instances
{
"text": Sai kha ya her kisi kay bus ki bat nhi hai lakin main ki hal kal bi Aj aur aj bi sirf Aus say bus,
"label": Positive
}
### Data Fields
<li>text: Roman Urdu text for sentimen analysis. (Data Type: String)</li>
<li>label: The sentiment label assigned to the text. (Data Type: String)</li>
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] |
Hunzla/crema-d-dataset | Hunzla | 2023-12-14T09:32:01Z | 3 | 0 | [
"region:us"
] | null | 2023-12-13T09:39:32Z | ---
dataset_info:
features:
- name: emotionG_label
dtype: string
- name: source
dtype: string
- name: gender
dtype: string
- name: emotion
dtype: string
- name: path
dtype: string
splits:
- name: train
num_bytes: 672189
num_examples: 6390
download_size: 54402
dataset_size: 672189
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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Hunzla/xls-r-crema-d-300-each-test | Hunzla | 2023-12-13T09:48:17Z | 3 | 0 | [
"region:us"
] | null | 2023-12-13T09:48:12Z | ---
dataset_info:
features:
- name: emotionG_label
dtype: string
- name: gender
dtype: string
- name: emotion
dtype: string
- name: path
dtype: string
- name: label
sequence: int64
- name: input_values
sequence:
sequence: float32
- name: input_length
dtype: int64
splits:
- name: train
num_bytes: 115298158
num_examples: 360
download_size: 103144258
dataset_size: 115298158
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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jtjt520j/cspider_for_chinese_llama2_1.3b | jtjt520j | 2023-12-13T12:48:31Z | 3 | 0 | [
"license:apache-2.0",
"region:us"
] | null | 2023-12-13T12:47:53Z | ---
license: apache-2.0
---
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sproos/summeval-sw | sproos | 2023-12-13T22:40:55Z | 3 | 0 | [
"region:us"
] | null | 2023-12-13T17:47:26Z | ---
dataset_info:
features:
- name: machine_summaries
sequence: string
- name: human_summaries
sequence: string
- name: relevance
sequence: float64
- name: coherence
sequence: float64
- name: fluency
sequence: float64
- name: consistency
sequence: float64
- name: text
dtype: string
- name: id
dtype: string
splits:
- name: train
num_bytes: 1172881
num_examples: 100
download_size: 484750
dataset_size: 1172881
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "summeval-sw"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Asude/IMDB_TR | Asude | 2023-12-13T19:43:44Z | 3 | 0 | [
"license:mit",
"region:us"
] | null | 2023-12-13T19:43:02Z | ---
license: mit
---
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Erynan/eval_virt_100 | Erynan | 2023-12-13T22:04:27Z | 3 | 0 | [
"region:us"
] | null | 2023-12-13T22:04:26Z | ---
dataset_info:
features:
- name: prompt
dtype: string
- name: response_a
dtype: string
- name: response_b
dtype: string
- name: more_reasonable
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 35885
num_examples: 100
download_size: 17660
dataset_size: 35885
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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DragonLine/ksponspeech_03 | DragonLine | 2023-12-14T12:38:55Z | 3 | 0 | [
"region:us"
] | null | 2023-12-14T07:52:58Z | ---
dataset_info:
features:
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: transcripts
dtype: string
splits:
- name: train
num_bytes: 18263712570.4
num_examples: 99200
- name: test
num_bytes: 2238637568.1
num_examples: 12400
- name: valid
num_bytes: 2199234088.1
num_examples: 12400
download_size: 20706993853
dataset_size: 22701584226.6
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: valid
path: data/valid-*
---
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Tippawan/test2-data-semi-p2 | Tippawan | 2023-12-15T03:36:38Z | 3 | 0 | [
"region:us"
] | null | 2023-12-14T09:54:21Z | ---
dataset_info:
features:
- name: tokens
sequence: string
- name: ner_tags
sequence: int64
- name: prob
sequence: float64
- name: ifpass
sequence: int64
- name: pred
dtype: int64
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 5228954
num_examples: 1833
download_size: 595046
dataset_size: 5228954
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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plncmm/cowese | plncmm | 2023-12-14T16:06:45Z | 3 | 0 | [
"region:us"
] | null | 2023-12-14T15:51:52Z | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 5713729755
num_examples: 2193338
download_size: 2350873989
dataset_size: 5713729755
---
# Dataset Card for "cowese"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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techandy42/ppo-200K-collected-dataset-steps-500 | techandy42 | 2023-12-14T15:55:43Z | 3 | 0 | [
"region:us"
] | null | 2023-12-14T15:55:39Z | ---
dataset_info:
features:
- name: observation
sequence:
sequence:
sequence: float32
- name: action
sequence: int64
- name: reward
sequence: float32
- name: done
sequence: bool
splits:
- name: train
num_bytes: 176769250
num_examples: 1162000
download_size: 30970817
dataset_size: 176769250
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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YujieW97/forest_grey | YujieW97 | 2023-12-14T17:21:05Z | 3 | 0 | [
"language:en",
"region:us"
] | null | 2023-12-14T16:18:38Z | ---
language:
- en
---
# Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
## Dataset Details
### Dataset Description
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- **Curated by:** Yujie Wu
- **Funded by [optional]:** EPFL
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### Direct Use
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[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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[More Information Needed]
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<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
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sproos/twitter-pairclass-fr | sproos | 2023-12-14T18:47:39Z | 3 | 0 | [
"region:us"
] | null | 2023-12-14T17:15:03Z | ---
dataset_info:
features:
- name: sent1
sequence: string
- name: sent2
sequence: string
- name: labels
sequence: int64
splits:
- name: train
num_bytes: 11962515
num_examples: 1
download_size: 4454872
dataset_size: 11962515
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "twitter-pairclass-fr"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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sproos/twitter-pairclass-sw | sproos | 2023-12-14T18:47:56Z | 3 | 0 | [
"region:us"
] | null | 2023-12-14T17:15:23Z | ---
dataset_info:
features:
- name: sent1
sequence: string
- name: sent2
sequence: string
- name: labels
sequence: int64
splits:
- name: train
num_bytes: 10795702
num_examples: 1
download_size: 4444037
dataset_size: 10795702
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "twitter-pairclass-sw"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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sproos/mindsmall-es | sproos | 2023-12-14T20:12:34Z | 3 | 0 | [
"region:us"
] | null | 2023-12-14T19:40:57Z | ---
dataset_info:
features:
- name: id
dtype: int64
- name: query
dtype: string
- name: positive
dtype: string
- name: negative
dtype: string
splits:
- name: train
num_bytes: 7361593
num_examples: 1419
download_size: 0
dataset_size: 7361593
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "mindsmall-es"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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sproos/mindsmall-fr | sproos | 2023-12-14T20:12:36Z | 3 | 0 | [
"region:us"
] | null | 2023-12-14T19:41:04Z | ---
dataset_info:
features:
- name: id
dtype: int64
- name: query
dtype: string
- name: positive
dtype: string
- name: negative
dtype: string
splits:
- name: train
num_bytes: 7896598
num_examples: 1419
download_size: 0
dataset_size: 7896598
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "mindsmall-fr"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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sproos/mindsmall-sw | sproos | 2023-12-14T22:59:39Z | 3 | 0 | [
"region:us"
] | null | 2023-12-14T22:59:34Z | ---
dataset_info:
features:
- name: id
dtype: int64
- name: query
dtype: string
- name: positive
dtype: string
- name: negative
dtype: string
splits:
- name: train
num_bytes: 6189574
num_examples: 1419
download_size: 3593810
dataset_size: 6189574
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "mindsmall-sw"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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madhaviit/NHAtestTime | madhaviit | 2023-12-15T00:20:09Z | 3 | 0 | [
"region:us"
] | null | 2023-12-15T00:20:07Z | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 13943775
num_examples: 10000
download_size: 5009157
dataset_size: 13943775
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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nlplabtdtu/edu_child_v1 | nlplabtdtu | 2023-12-15T03:38:16Z | 3 | 0 | [
"region:us"
] | null | 2023-12-15T03:38:04Z | ---
dataset_info:
features:
- name: content
dtype: string
- name: metadata
struct:
- name: metadata
struct:
- name: filename
dtype: string
- name: id
dtype: string
- name: seq_num
dtype: int64
- name: source
dtype: string
- name: uni_id
dtype: string
- name: vector
sequence: float64
splits:
- name: train
num_bytes: 75351083
num_examples: 5824
download_size: 55166789
dataset_size: 75351083
configs:
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data_files:
- split: train
path: data/train-*
---
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Tippawan/test2-data-semi-p1-WLV | Tippawan | 2023-12-15T07:32:40Z | 3 | 0 | [
"region:us"
] | null | 2023-12-15T07:32:36Z | ---
dataset_info:
features:
- name: tokens
sequence: string
- name: ner_tags
sequence: int64
- name: prob
sequence: float64
- name: ifpass
sequence: int64
- name: pred
dtype: int64
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 13689111
num_examples: 10898
download_size: 2022133
dataset_size: 13689111
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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Tippawan/test2-data-semi-trainulb-r3-WLV | Tippawan | 2023-12-15T09:20:56Z | 3 | 0 | [
"region:us"
] | null | 2023-12-15T09:20:50Z | ---
dataset_info:
features:
- name: tokens
sequence: string
- name: ner_tags
sequence: int64
- name: prob
sequence: float64
- name: ifpass
sequence: int64
- name: pred
dtype: int64
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 124300291
num_examples: 35705
download_size: 29092338
dataset_size: 124300291
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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tdh87/Test | tdh87 | 2023-12-15T09:47:10Z | 3 | 0 | [
"license:apache-2.0",
"region:us"
] | null | 2023-12-15T09:46:32Z | ---
license: apache-2.0
---
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HowMannyMore/romanurdu-sentiment-dataset-v3 | HowMannyMore | 2023-12-15T10:40:29Z | 3 | 0 | [
"region:us"
] | null | 2023-12-15T10:40:26Z | ---
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype: string
splits:
- name: train
num_bytes: 5460912
num_examples: 60190
- name: test
num_bytes: 1127574
num_examples: 12497
- name: valid
num_bytes: 971174
num_examples: 10622
download_size: 5139189
dataset_size: 7559660
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: valid
path: data/valid-*
---
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krishan-CSE/Unified_Dataset_ROBERTA | krishan-CSE | 2023-12-15T11:44:31Z | 3 | 0 | [
"license:apache-2.0",
"region:us"
] | null | 2023-12-15T11:44:14Z | ---
license: apache-2.0
---
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