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class | tags
sequence | description
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5.93k
⌀ | downloads
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1.14M
| likes
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1.79k
|
|---|---|---|---|---|---|
PanoEvJ/GenAI-sample | false | [] | null | 0 | 0 |
abidlabs/abc-love | false | [] | null | 0 | 0 |
Seyfelislem/cv_11_arabic_test_noisy_II | false | [] | null | 0 | 0 |
abidlabs/abc-love2 | false | [] | null | 0 | 0 |
datablations/mup2 | false | [] | null | 0 | 0 |
Krzysko1/komandiero_bombardiero | false | [
"license:cc-by-nc-4.0"
] | null | 0 | 0 |
amishshah/slay | false | [] | null | 0 | 0 |
amishshah/imbalanced_0 | false | [] | null | 0 | 0 |
amishshah/imbalanced_1 | false | [] | null | 0 | 0 |
amishshah/imbalanced_2 | false | [] | null | 0 | 0 |
amishshah/imbalanced_3 | false | [] | null | 0 | 0 |
Dampish/Proccessed-GPT-NEO | false | [
"license:cc-by-nc-4.0"
] | null | 0 | 0 |
amishshah/imbalanced_4 | false | [] | null | 0 | 0 |
ashwinR/ChatgptExplanation | false | [
"license:mit"
] | null | 0 | 0 |
amishshah/imbalanced_5 | false | [] | null | 0 | 0 |
amishshah/imbalanced_6 | false | [] | null | 0 | 0 |
amishshah/imbalanced_7 | false | [] | null | 0 | 0 |
amishshah/imbalanced_8 | false | [] | null | 0 | 0 |
amishshah/imbalanced_9 | false | [] | null | 0 | 0 |
KyonBS/fudatsukiKyoukoIA-dataset | false | [] | null | 0 | 0 |
DevAibest/alpaca_json_data | false | [
"license:afl-3.0"
] | null | 0 | 0 |
vmalperovich/QC | false | [
"task_categories:text-classification",
"size_categories:1K<n<10K",
"language:en",
"license:mit"
] | This data collection contains all the data used in our learning question classification experiments(see [1]), which has question class definitions, the training and testing question sets, examples of preprocessing the questions, feature definition scripts and examples of semantically related word features.
This work has been done by Xin Li and Dan Roth and supported by [2]. | 0 | 0 |
norabelrose/truthful_qa_mc | false | [
"license:apache-2.0"
] | null | 0 | 0 |
norabelrose/truthful_qa | false | [
"license:apache-2.0"
] | TruthfulQA is a benchmark to measure whether a language model is truthful in
generating answers to questions. The benchmark comprises 817 questions that
span 38 categories, including health, law, finance and politics. Questions are
crafted so that some humans would answer falsely due to a false belief or
misconception. To perform well, models must avoid generating false answers
learned from imitating human texts. | 0 | 0 |
jimzhiwei/amazon_product | false | [
"license:openrail"
] | null | 0 | 0 |
iamketan25/roleplay-instructions-dataset | false | [] | null | 0 | 0 |
AlekseyKorshuk/dummy-conversation-with-system | false | [] | null | 0 | 0 |
henri28/Hague180Conventionptbr-fr | false | [] | null | 0 | 0 |
tejasbale02/JohnWickCollection | false | [] | null | 0 | 0 |
shawnwork/ttmnist | false | [] | null | 0 | 0 |
shawnwork/ttmnist1 | false | [] | null | 0 | 0 |
Esgbdf/1 | false | [] | null | 0 | 0 |
KyonBS/kunoTsubIA-dataset | false | [] | null | 0 | 0 |
KmAnu/CT1 | false | [] | null | 0 | 0 |
shawnwork/test_final | false | [] | null | 0 | 0 |