id stringlengths 2 115 | author stringlengths 2 42 ⌀ | last_modified timestamp[us, tz=UTC] | downloads int64 0 8.87M | likes int64 0 3.84k | paperswithcode_id stringlengths 2 45 ⌀ | tags list | lastModified timestamp[us, tz=UTC] | createdAt stringlengths 24 24 | key stringclasses 1 value | created timestamp[us] | card stringlengths 1 1.01M | embedding list | library_name stringclasses 21 values | pipeline_tag stringclasses 27 values | mask_token null | card_data null | widget_data null | model_index null | config null | transformers_info null | spaces null | safetensors null | transformersInfo null | modelId stringlengths 5 111 ⌀ | embeddings list |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
xFrisky02/prezentacje | xFrisky02 | 2023-11-28T17:37:54Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T17:37:54Z | 2023-11-28T17:37:23.000Z | 2023-11-28T17:37:23 | Entry not found | [
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nguyenthanhdo/orca-cqa-v1.0 | nguyenthanhdo | 2023-11-28T18:38:00Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T18:38:00Z | 2023-11-28T17:46:40.000Z | 2023-11-28T17:46:40 | ---
configs:
- config_name: default
data_files:
- split: gpt3.5
path: data/gpt3.5-*
- split: gpt4
path: data/gpt4-*
dataset_info:
features:
- name: id
dtype: string
- name: system_prompt
dtype: string
- name: question
dtype: string
- name: response
dtype: string
- name: question_word_count
dtype: int64
- name: response_word_count
dtype: int64
splits:
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num_bytes: 721493280.2090137
num_examples: 426091
- name: gpt4
num_bytes: 199603726.6207845
num_examples: 110053
download_size: 1074570511
dataset_size: 921097006.8297982
---
```py
from datasets import load_dataset
cqa_signs = [
"based on the context",
"based on the given",
"based on the article",
# "given the following article",
"following article",
"above article",
"given the following passage",
"is inside the article"
]
mqa_signs = [
"Options:",
"Choose from:",
"Write an article based on this summary",
"select the best answer"
]
orca = load_dataset("Open-Orca/OpenOrca", data_files={
"gpt3.5": "3_5M-GPT3_5-Augmented.parquet",
"gpt4": "1M-GPT4-Augmented.parquet"
})
def word_count(example):
question, response = example["question"], example["response"]
result = dict(
question_word_count=len(question.split()),
response_word_count=len(response.split())
)
return result
orca = orca.map(word_count)
keywords = ["article", "context", "passage", "summa", "paragraph"]
def get_closed_qa(example):
input = example["question"].lower()
flag = False
if sum([1 for k in keywords if k in input]):
flag = True
return flag
orca1 = orca.filter(get_closed_qa)
def get_closed_qa2(example):
"""
Exclude multiple choice questions and filter by length.
"""
mqa_signs = [
"Options:",
"OPTIONS:",
"[+]", "[-]",
"Choose from:",
"Choices:",
"select the best answer",
"Pick from",
]
flag = False
qwc, rwc = example["question_word_count"], example["response_word_count"]
if qwc > 200 and rwc < 300:
flag = True
if qwc < rwc:
flag = False
if any([sign in example["question"] for sign in mqa_signs]):
flag = False
return flag
orca2 = orca1.filter(get_closed_qa2)
orca2.push_to_hub("nguyenthanhdo/orca-cqa-v1.0")
``` | [
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jaozindacdd/chiquinho | jaozindacdd | 2023-11-28T18:15:36Z | 0 | 0 | null | [
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"region:us"
] | 2023-11-28T18:15:36Z | 2023-11-28T17:47:03.000Z | 2023-11-28T17:47:03 | ---
license: openrail
---
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afcarvallo/mapudungun_transcription_lafkenche_splitted | afcarvallo | 2023-11-28T18:02:48Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T18:02:48Z | 2023-11-28T17:48:47.000Z | 2023-11-28T17:48:47 | ---
dataset_info:
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configs:
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data_files:
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path: data/train-*
- split: test
path: data/test-*
---
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martymukherjee/poisson2d | martymukherjee | 2023-11-28T17:58:07Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | 2023-11-28T17:58:07Z | 2023-11-28T17:58:07.000Z | 2023-11-28T17:58:07 | ---
license: mit
---
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Oscaraandersson/reveal | Oscaraandersson | 2023-11-28T18:08:03Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T18:08:03Z | 2023-11-28T18:07:57.000Z | 2023-11-28T18:07:57 | ---
dataset_info:
features:
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dtype: string
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names:
'0': 'False'
'1': 'True'
splits:
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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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AFK47/TRIZB | AFK47 | 2023-11-28T18:10:52Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T18:10:52Z | 2023-11-28T18:10:51.000Z | 2023-11-28T18:10:51 | Entry not found | [
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kaikaih/nva-mizusima | kaikaih | 2023-11-28T18:12:43Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T18:12:43Z | 2023-11-28T18:12:25.000Z | 2023-11-28T18:12:25 | Invalid username or password. | [
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... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
kaikaih/nva-yosizawa | kaikaih | 2023-11-28T18:13:35Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T18:13:35Z | 2023-11-28T18:13:12.000Z | 2023-11-28T18:13:12 | Invalid username or password. | [
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... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
hjgp/line_louver | hjgp | 2023-11-28T18:41:47Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T18:41:47Z | 2023-11-28T18:24:42.000Z | 2023-11-28T18:24:42 | Entry not found | [
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-0... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
ThWu/cleaned_prompt_r_2 | ThWu | 2023-11-28T18:25:03Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T18:25:03Z | 2023-11-28T18:24:54.000Z | 2023-11-28T18:24:54 | ---
dataset_info:
features:
- name: conversations
sequence: string
splits:
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num_bytes: 156626089.82132664
num_examples: 266593
download_size: 90801143
dataset_size: 156626089.82132664
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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HossainRabby/MedicalDataset | HossainRabby | 2023-11-28T18:28:08Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T18:28:08Z | 2023-11-28T18:27:36.000Z | 2023-11-28T18:27:36 | ---
dataset_info:
features:
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dtype: string
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sequence: int32
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sequence: int8
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configs:
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data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
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hodgesz/validated-sql-create-context | hodgesz | 2023-11-28T18:37:00Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | 2023-11-28T18:37:00Z | 2023-11-28T18:29:41.000Z | 2023-11-28T18:29:41 | ---
license: apache-2.0
---
| [
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-0.0478255338966846... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
islamrokon/TrainDataset | islamrokon | 2023-11-28T18:36:33Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T18:36:33Z | 2023-11-28T18:36:14.000Z | 2023-11-28T18:36:14 | ---
dataset_info:
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dtype: string
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dtype: string
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sequence: int32
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sequence: int8
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sequence: int64
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num_bytes: 8104968.91278113
num_examples: 1641
download_size: 26912462
dataset_size: 81034872.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
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namngo/viquad-t-vinews-js | namngo | 2023-11-28T18:37:58Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T18:37:58Z | 2023-11-28T18:37:03.000Z | 2023-11-28T18:37:03 | Entry not found | [
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-... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
MITCriticalData/cloud2cloudless_dataset_5_municipalities | MITCriticalData | 2023-11-28T19:09:36Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | 2023-11-28T19:09:36Z | 2023-11-28T18:42:07.000Z | 2023-11-28T18:42:07 | ---
license: mit
---
# Creating Cloud-Cloudless Paired Dataset
To generate the Cloud-Cloudless Paired Dataset, we utilize an existing dataset that encompasses imagery from five municipalities in Colombia. This dataset is structured with each municipality containing 165 images, acquired through the satellite_extractor API and based on SentinelHub, spanning across 12 different channels. Within each municipality, we have meticulously identified the optimal cloudless image and stored the corresponding names in a dictionary called `cloudless_groundtruths`.
The primary objective is to subtract this specific cloudless image from the set of 165 images, resulting in 164 images per municipality. Subsequently, each of these 164 images will be paired with the previously identified cloudless image. Consequently, this process creates a total of `164 * 2 * NUM_MUNICIPALITIES`, yielding 1640 images or 820 image pairs in total.
To facilitate this dataset creation, we have introduced the class `Cloud2CloudlesDataset`. This class replicates each corresponding ground truth for the 164 images in each municipality, storing every paired set in a newly designated folder named `DATASET`.
Originally, the images were formatted as `image_DD%%MM%%YY`. As part of the dataset creation process, we will rename these images to `image_DD%%MM%%YY_gt` for the ground truth image and `image_DD%%MM%%YY_cloud` for the image with clouds.
Upon initialization, the class requires the path to the source dataset, which contains raw images for each municipality organized in N folders, and the final path where the new dataset will be stored.
The implementation includes thorough testing to verify the number of images, ensuring that the final count aligns with the total number of images encountered in the source folder path. Additionally, one of the functions within this class ensures the existence of each folder in the specified destination path, guaranteeing a well-organized and comprehensive Cloud-Cloudless Paired Dataset.
Github code [here](https://github.com/sebasmos/satellite.extractor/blob/main/notebooks/create_Cloud2CloudlesDataset.ipynb): | [
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Gonzaluigi/your-dataset-name | Gonzaluigi | 2023-11-28T18:42:33Z | 0 | 0 | null | [
"region:us"
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ThomET/common_voice_13_0_fr_pseudo_labelled | ThomET | 2023-11-28T18:46:40Z | 0 | 0 | null | [
"region:us"
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-... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
cyrilzhang/perturbed-explanations-tiny | cyrilzhang | 2023-11-28T18:47:57Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T18:47:57Z | 2023-11-28T18:46:45.000Z | 2023-11-28T18:46:45 | ---
dataset_info:
features:
- name: query
dtype: string
- name: response
dtype: string
- name: response_worse
dtype: string
splits:
- name: train
num_bytes: 10701.0
num_examples: 18
- name: test
num_bytes: 1189.0
num_examples: 2
download_size: 0
dataset_size: 11890.0
---
# Dataset Card for "perturbed-explanations-tiny"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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-0.2101538479328155... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
nguyenthanhdo/orca-unanswerable-v2.0 | nguyenthanhdo | 2023-11-28T19:27:52Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T19:27:52Z | 2023-11-28T18:52:24.000Z | 2023-11-28T18:52:24 | ---
configs:
- config_name: default
data_files:
- split: long_excuse
path: data/long_excuse-*
- split: short_excuse
path: data/short_excuse-*
dataset_info:
features:
- name: id
dtype: string
- name: system_prompt
dtype: string
- name: question
dtype: string
- name: response
dtype: string
- name: question_word_count
dtype: int64
- name: response_word_count
dtype: int64
- name: from
dtype: string
splits:
- name: long_excuse
num_bytes: 90070208.6254609
num_examples: 34520
- name: short_excuse
num_bytes: 107366715.3745391
num_examples: 41149
download_size: 117180271
dataset_size: 197436924.0
---
```py
from datasets import load_dataset
import unicodedata as ud
uns = [
"is not mentioned",
"insufficient",
"not sufficient",
"is not provided",
"does not provide",
"does not mention",
"not clear",
"not possible",
"not enough",
"impossible",
"not explicitly mentioned"
]
def get_uns(example):
output = example["response"].lower()
output = ud.normalize("NFC", output)
flag = False
if any([sign in output for sign in uns]):
flag = True
return flag
orca_cqa = load_dataset("nguyenthanhdo/orca-cqa-v1.0")
orca_uns = orca_cqa.filter(get_uns)
from datasets import concatenate_datasets
x, y = orca_uns["gpt3.5"], orca_uns["gpt4"]
x = x.add_column("from", ["gpt3.5" for _ in x])
y = y.add_column("from", ["gpt4" for _ in y])
one_uns = concatenate_datasets([x, y])
def get_long_excuse(example):
response = example["response"]
n_sents = len([s for s in response.split(".") if s.strip()])
return n_sents >= 2
def get_short_excuse(example):
response = example["response"]
n_sents = len([s for s in response.split(".") if s.strip()])
return n_sents <= 1
long_uns = one_uns.filter(get_long_excuse)
short_uns = one_uns.filter(get_short_excuse)
from datasets import DatasetDict
divided_uns = DatasetDict({
"long_excuse": long_uns,
"short_excuse": short_uns
})
divided_uns.push_to_hub("nguyenthanhdo/orca-unanswerable-v2.0")
``` | [
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hanamy2/langchain_test | hanamy2 | 2023-11-28T18:56:56Z | 0 | 0 | null | [
"region:us"
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YaminiMahesh/erpbot | YaminiMahesh | 2023-11-28T18:57:27Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T18:57:27Z | 2023-11-28T18:57:27.000Z | 2023-11-28T18:57:27 | Entry not found | [
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MelioAI/safety-qa-sample | MelioAI | 2023-11-28T19:06:45Z | 0 | 0 | null | [
"license:cc-by-nc-4.0",
"region:us"
] | 2023-11-28T19:06:45Z | 2023-11-28T19:02:26.000Z | 2023-11-28T19:02:26 | ---
license: cc-by-nc-4.0
dataset_info:
features:
- name: question
dtype: string
- name: answers
dtype: string
splits:
- name: train
num_bytes: 43233.06
num_examples: 100
- name: valid
num_bytes: 43233.06
num_examples: 100
- name: test
num_bytes: 43233.06
num_examples: 100
download_size: 96735
dataset_size: 129699.18
---
This is a very small sample from PKU-Alignment/PKU-SafeRLHF-10K that has been processed for QA. | [
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bomdey/plAInLang | bomdey | 2023-11-28T19:35:07Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T19:35:07Z | 2023-11-28T19:15:48.000Z | 2023-11-28T19:15:48 | Entry not found | [
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namngo/viquad-t-vico | namngo | 2023-11-28T19:23:18Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T19:23:18Z | 2023-11-28T19:22:18.000Z | 2023-11-28T19:22:18 | Entry not found | [
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something-else/Slim-RWKV | something-else | 2023-11-28T19:23:51Z | 0 | 0 | null | [
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FanjiaYan/CS182-DreamBooth-dataset | FanjiaYan | 2023-11-28T19:28:50Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | 2023-11-28T19:28:50Z | 2023-11-28T19:24:29.000Z | 2023-11-28T19:24:29 | ---
license: apache-2.0
---
| [
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venkat-srinivasan-nexusflow/multiapi_prototype_Climate | venkat-srinivasan-nexusflow | 2023-11-28T19:25:28Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T19:25:28Z | 2023-11-28T19:25:27.000Z | 2023-11-28T19:25:27 | Entry not found | [
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venkat-srinivasan-nexusflow/openai_gpt4_Climate | venkat-srinivasan-nexusflow | 2023-11-28T19:28:43Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T19:28:43Z | 2023-11-28T19:28:42.000Z | 2023-11-28T19:28:42 | Entry not found | [
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paul-w-qs/contracts_v8 | paul-w-qs | 2023-11-28T19:34:17Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T19:34:17Z | 2023-11-28T19:32:45.000Z | 2023-11-28T19:32:45 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: image
dtype: image
- name: TABLE_STYLE
dtype: string
- name: JSON_LABEL
dtype: string
- name: DICT_LABEL
dtype: string
- name: question
dtype: string
- name: answer
dtype: string
splits:
- name: train
num_bytes: 265764399.424
num_examples: 3904
download_size: 253696091
dataset_size: 265764399.424
---
# Dataset Card for "contracts_v8"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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mattlc/medical_internal_eval_28_nov_2023 | mattlc | 2023-11-28T20:44:11Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T20:44:11Z | 2023-11-28T19:34:13.000Z | 2023-11-28T19:34:13 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: description
dtype: string
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dtype: string
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dtype: bool
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dtype: string
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dtype: string
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sequence: string
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list:
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dtype: string
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dtype: string
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dtype: string
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dtype: string
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dtype: string
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dtype: string
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dtype: string
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list:
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dtype: string
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dtype:
audio:
sampling_rate: 16000
- name: duration
dtype: float64
splits:
- name: train
num_bytes: 209449490.0
num_examples: 635
- name: test
num_bytes: 51106043.0
num_examples: 159
download_size: 242348993
dataset_size: 260555533.0
---
# Dataset Card for "medical_internal_eval_28_nov_2023"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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-0.013603956438601017... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
316usman/tapal_dataset_demo | 316usman | 2023-11-28T19:44:20Z | 0 | 0 | null | [
"license:bsd",
"region:us"
] | 2023-11-28T19:44:20Z | 2023-11-28T19:41:58.000Z | 2023-11-28T19:41:58 | ---
license: bsd
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 205593.2356557377
num_examples: 878
- name: test
num_bytes: 22947.764344262294
num_examples: 98
download_size: 107745
dataset_size: 228541.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
| [
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-0.0478260256350... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
Tim793/MCQ_Aussagen | Tim793 | 2023-11-28T19:44:58Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | 2023-11-28T19:44:58Z | 2023-11-28T19:43:00.000Z | 2023-11-28T19:43:00 | ---
license: apache-2.0
---
| [
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gmongaras/BERT_Base_Cased_512_Dataset_Mapped | gmongaras | 2023-11-28T19:43:59Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T19:43:59Z | 2023-11-28T19:43:32.000Z | 2023-11-28T19:43:32 | Dataset using the bert-cased tokenizer, cutoff sentences to 512 length (not sentence pairs), all sentence pairs extracted.
Original datasets:
https://huggingface.co/datasets/bookcorpus
https://huggingface.co/datasets/wikipedia Variant: 20220301.en
Mapped from: https://huggingface.co/datasets/gmongaras/BERT_Base_Cased_512_Dataset | [
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ramosramon433/adsa | ramosramon433 | 2023-11-28T22:16:07Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | 2023-11-28T22:16:07Z | 2023-11-28T19:51:55.000Z | 2023-11-28T19:51:55 | ---
license: apache-2.0
---
| [
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DZN222/joaocaetano | DZN222 | 2023-11-28T19:57:01Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-28T19:57:01Z | 2023-11-28T19:53:12.000Z | 2023-11-28T19:53:12 | ---
license: openrail
---
| [
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BangumiBase/nodamecantabile | BangumiBase | 2023-11-28T22:32:30Z | 0 | 0 | null | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | 2023-11-28T22:32:30Z | 2023-11-28T19:55:05.000Z | 2023-11-28T19:55:05 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Nodame Cantabile
This is the image base of bangumi Nodame Cantabile, we detected 31 characters, 5634 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 281 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 181 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 1138 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 217 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 1479 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 373 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 553 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 126 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 116 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 158 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 56 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 35 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 36 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 130 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 73 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 54 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 28 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 52 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 71 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 39 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 44 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 76 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 46 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 60 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 19 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 16 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 31 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 18 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 17 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 7 | [Download](29/dataset.zip) |  |  |  |  |  |  |  | N/A |
| noise | 104 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| [
-0.7073027491569519,
-0.1371411383152008,
0.1457647830247879,
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-0.7244716882705688,
0.516594648361206,... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
BangumiBase/mahoushoujoprettysammy | BangumiBase | 2023-11-28T20:48:31Z | 0 | 0 | null | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | 2023-11-28T20:48:31Z | 2023-11-28T19:56:15.000Z | 2023-11-28T19:56:15 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Mahou Shoujo Pretty Sammy
This is the image base of bangumi Mahou Shoujo Pretty Sammy, we detected 37 characters, 2360 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 857 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 73 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 15 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 17 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 51 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 18 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 129 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 24 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 23 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 83 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 21 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 17 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 9 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 9 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 59 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 22 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 19 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 35 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 10 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 7 | [Download](19/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 20 | 40 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 5 | [Download](21/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| 22 | 12 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 35 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 12 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 94 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 168 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 49 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 27 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 11 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 8 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 13 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 61 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 212 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 25 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 5 | [Download](35/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| noise | 85 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| [
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0.536378502845764... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
sam1120/merged-safety-ns1-utcustom-train-v1.0 | sam1120 | 2023-11-28T19:58:40Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T19:58:40Z | 2023-11-28T19:57:12.000Z | 2023-11-28T19:57:12 | ---
dataset_info:
features:
- name: name
dtype: string
- name: pixel_values
dtype: image
- name: labels
dtype: image
splits:
- name: train
num_bytes: 2904492356.0
num_examples: 224
download_size: 719471263
dataset_size: 2904492356.0
---
# Dataset Card for "merged-safety-ns1-utcustom-train-v1.0"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Gabriel1322/minimessi | Gabriel1322 | 2023-11-28T20:01:58Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-28T20:01:58Z | 2023-11-28T20:01:45.000Z | 2023-11-28T20:01:45 | ---
license: openrail
---
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BubbleJoe/bootstrap_sms | BubbleJoe | 2023-11-28T20:05:51Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T20:05:51Z | 2023-11-28T20:05:50.000Z | 2023-11-28T20:05:50 | ---
dataset_info:
features:
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splits:
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num_bytes: 473170
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download_size: 106042
dataset_size: 473170
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "bootstrap_sms"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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ThanhMai/Clips_dataset | ThanhMai | 2023-11-28T20:57:41Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T20:57:41Z | 2023-11-28T20:06:17.000Z | 2023-11-28T20:06:17 | ---
dataset_info:
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dataset_size: 952667.0
configs:
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---
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MaryDatascientist/en_dataset | MaryDatascientist | 2023-11-28T20:08:22Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T20:08:22Z | 2023-11-28T20:08:16.000Z | 2023-11-28T20:08:16 | Entry not found | [
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BangumiBase/hinamatsuri | BangumiBase | 2023-11-28T21:12:18Z | 0 | 0 | null | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | 2023-11-28T21:12:18Z | 2023-11-28T20:08:48.000Z | 2023-11-28T20:08:48 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Hinamatsuri
This is the image base of bangumi Hinamatsuri, we detected 23 characters, 1820 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 107 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 93 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 11 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 342 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 216 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 40 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 27 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 90 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 39 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 24 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 28 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 64 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 30 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 284 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 51 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 14 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 217 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 28 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 25 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 9 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 30 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 8 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 43 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
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gagan3012/alama_training_data | gagan3012 | 2023-11-28T20:11:22Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T20:11:22Z | 2023-11-28T20:11:22.000Z | 2023-11-28T20:11:22 | Entry not found | [
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... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
vwxyzjn/summarize_from_feedback_oai_preprocessing_gpt2_153 | vwxyzjn | 2023-11-28T20:18:30Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T20:18:30Z | 2023-11-28T20:17:54.000Z | 2023-11-28T20:17:54 | ---
dataset_info:
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num_examples: 86086
download_size: 125420707
dataset_size: 1834552536
---
# Dataset Card for "summarize_from_feedback_oai_preprocessing_gpt2_153"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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MaryDatascientist/test | MaryDatascientist | 2023-11-28T20:22:01Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T20:22:01Z | 2023-11-28T20:21:37.000Z | 2023-11-28T20:21:37 | ---
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trolllemon/dogs | trolllemon | 2023-11-28T23:30:13Z | 0 | 0 | null | [
"task_categories:image-classification",
"language:en",
"license:mit",
"region:us"
] | 2023-11-28T23:30:13Z | 2023-11-28T20:25:35.000Z | 2023-11-28T20:25:35 | ---
language:
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license: mit
task_categories:
- image-classification
pretty_name: Dogs
dataset_info:
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dtype: string
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splits:
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download_size: 3572
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configs:
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data_files:
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path: data/train-*
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path: data/test-*
---
| [
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# Dataset Card for "summarize_from_feedback_tldr_3_filtered_oai_preprocessing_pythia-160m_53"
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# Dataset Card for "summarize_from_feedback_oai_preprocessing_pythia-160m_169"
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# Dataset Card for "es-2811-no-demoji-m"
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configs:
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data_files:
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path: data/train-*
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path: data/validation-*
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path: data/test-*
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cjtita64/JhonnyOrosco | cjtita64 | 2023-11-28T22:56:22Z | 0 | 0 | null | [
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Apinapi/LucasD | Apinapi | 2023-11-28T21:46:04Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-28T21:46:04Z | 2023-11-28T21:45:35.000Z | 2023-11-28T21:45:35 | ---
license: openrail
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Gaxys/PD_Books | Gaxys | 2023-11-28T23:43:40Z | 0 | 0 | null | [
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] | 2023-11-28T23:43:40Z | 2023-11-28T21:51:11.000Z | 2023-11-28T21:51:11 | ---
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alaeddinehamroun/invoices-custom-data-processed | alaeddinehamroun | 2023-11-28T21:52:05Z | 0 | 0 | null | [
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trolllemon/dogs-train | trolllemon | 2023-11-28T21:54:18Z | 0 | 0 | null | [
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trolllemon/dogs-test | trolllemon | 2023-11-28T21:54:20Z | 0 | 0 | null | [
"region:us"
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CoderBose/reddit-demo | CoderBose | 2023-11-28T22:18:21Z | 0 | 0 | null | [
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Ahmeddakaa/Atlantic_hurrican | Ahmeddakaa | 2023-11-28T22:14:03Z | 0 | 0 | null | [
"region:us"
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umm-maybe/wikisource-cthulhu-mythos | umm-maybe | 2023-11-28T22:54:49Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T22:54:49Z | 2023-11-28T22:15:17.000Z | 2023-11-28T22:15:17 | ---
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manu/french_poetry | manu | 2023-11-28T22:24:06Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T22:24:06Z | 2023-11-28T22:18:48.000Z | 2023-11-28T22:18:48 | ---
dataset_info:
features:
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dtype: string
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splits:
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download_size: 2072389
dataset_size: 3286614
---
# Dataset Card for "french_poetry"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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royzhong/one-word | royzhong | 2023-11-28T22:39:59Z | 0 | 0 | null | [
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xwjzds/pretrain_sts_extend | xwjzds | 2023-11-28T22:44:27Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T22:44:27Z | 2023-11-28T22:44:25.000Z | 2023-11-28T22:44:25 | ---
dataset_info:
features:
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---
# Dataset Card for "pretrain_sts_extend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Apinapi/LucasDA | Apinapi | 2023-11-28T22:48:37Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-28T22:48:37Z | 2023-11-28T22:47:20.000Z | 2023-11-28T22:47:20 | ---
license: openrail
---
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toninhodjj/FLAKESPOWER | toninhodjj | 2023-11-28T22:48:24Z | 0 | 0 | null | [
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license: openrail
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Gabriel1322/messimini | Gabriel1322 | 2023-11-28T22:56:32Z | 0 | 0 | null | [
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Apinapi/Lucas12 | Apinapi | 2023-11-28T22:56:07Z | 0 | 0 | null | [
"license:openrail",
"region:us"
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Apinapi/LDA | Apinapi | 2023-11-28T23:01:38Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-28T23:01:38Z | 2023-11-28T23:01:17.000Z | 2023-11-28T23:01:17 | ---
license: openrail
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proculation/mytestds | proculation | 2023-11-28T23:08:57Z | 0 | 0 | null | [
"license:unknown",
"region:us"
] | 2023-11-28T23:08:57Z | 2023-11-28T23:08:57.000Z | 2023-11-28T23:08:57 | ---
license: unknown
---
| [
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mlabonne/chatml_dpo_pairs | mlabonne | 2023-11-28T23:27:55Z | 0 | 1 | null | [
"task_categories:text-generation",
"task_categories:question-answering",
"task_categories:summarization",
"task_categories:conversational",
"size_categories:10K<n<100K",
"license:apache-2.0",
"arxiv:2306.02707",
"region:us"
] | 2023-11-28T23:27:55Z | 2023-11-28T23:22:38.000Z | 2023-11-28T23:22:38 | ---
dataset_info:
features:
- name: prompt
dtype: string
- name: chosen
dtype: string
- name: rejected
dtype: string
splits:
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num_bytes: 35914686
num_examples: 12859
download_size: 19539811
dataset_size: 35914686
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: apache-2.0
task_categories:
- text-generation
- question-answering
- summarization
- conversational
pretty_name: ChatML DPO Pairs
size_categories:
- 10K<n<100K
---
# ChatML DPO Pairs
This is a preprocessed version of [Intel/orca_dpo_pairs](https://huggingface.co/datasets/Intel/orca_dpo_pairs) using the [ChatML](https://huggingface.co/docs/transformers/chat_templating) format.
Like the original dataset, it contains 12k examples from [Orca](https://arxiv.org/abs/2306.02707) style dataset [Open-Orca/OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca).
Here is the code used to preprocess it:
```python
def chatml_format(example):
# Format system
if len(example['system']) > 0:
message = {"role": "system", "content": example['system']}
system = tokenizer.apply_chat_template([message], tokenize=False)
else:
system = ""
# Format instruction
message = {"role": "user", "content": example['question']}
prompt = tokenizer.apply_chat_template([message], tokenize=False, add_generation_prompt=True)
# Format chosen answer
chosen = example['chatgpt'] + "<|im_end|>\n"
# Format rejected answer
rejected = example['llama2-13b-chat'] + "<|im_end|>\n"
return {
"prompt": system + prompt,
"chosen": chosen,
"rejected": rejected,
}
# Load dataset
dataset = load_dataset("Intel/orca_dpo_pairs")['train']
# Save columns
original_columns = dataset.column_names
# Tokenizer
tokenizer = AutoTokenizer.from_pretrained("teknium/OpenHermes-2.5-Mistral-7B")
tokenizer.pad_token = tokenizer.eos_token
tokenizer.padding_side = "left"
# Format dataset
dataset = dataset.map(
chatml_format,
remove_columns=original_columns
)
``` | [
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gvozdev/test_v | gvozdev | 2023-11-28T23:42:43Z | 0 | 0 | null | [
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Thiagovmsc/Ramona | Thiagovmsc | 2023-11-28T23:43:14Z | 0 | 0 | null | [
"license:openrail",
"region:us"
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license: openrail
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utkarsh-mujumdar/speech_accent_archive_dataset | utkarsh-mujumdar | 2023-11-28T23:46:48Z | 0 | 0 | null | [
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dataset_info:
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Racso777/Mushroom_Dataset | Racso777 | 2023-11-29T00:06:58Z | 0 | 0 | null | [
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kaikaih/nva-okada | kaikaih | 2023-11-29T00:05:49Z | 0 | 0 | null | [
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khanhlinh/eurosat | khanhlinh | 2023-11-29T00:11:09Z | 0 | 0 | null | [
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kaikaih/nva-miyazawa | kaikaih | 2023-11-29T00:07:16Z | 0 | 0 | null | [
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kaikaih/nva-ran | kaikaih | 2023-11-29T00:08:36Z | 0 | 0 | null | [
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kaikaih/nva-miurar | kaikaih | 2023-11-29T00:10:39Z | 0 | 0 | null | [
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] | 2023-11-29T00:10:39Z | 2023-11-29T00:10:16.000Z | 2023-11-29T00:10:16 | Entry not found | [
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phms/Vidal | phms | 2023-11-29T00:59:24Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T00:59:24Z | 2023-11-29T00:10:16.000Z | 2023-11-29T00:10:16 | Entry not found | [
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jaimik69/graphcore-vqa-100 | jaimik69 | 2023-11-29T00:10:44Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T00:10:44Z | 2023-11-29T00:10:44.000Z | 2023-11-29T00:10:44 | Entry not found | [
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rollstar/marcosantonio | rollstar | 2023-11-29T00:12:10Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-29T00:12:10Z | 2023-11-29T00:12:10.000Z | 2023-11-29T00:12:10 | ---
license: openrail
---
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benayas/snips_llm_v0 | benayas | 2023-11-29T00:13:01Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T00:13:01Z | 2023-11-29T00:12:59.000Z | 2023-11-29T00:12:59 | ---
dataset_info:
features:
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dtype: string
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splits:
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dataset_size: 10368128
configs:
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data_files:
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RIW/butterfly_wm_100_1 | RIW | 2023-11-29T00:16:15Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T00:16:15Z | 2023-11-29T00:16:08.000Z | 2023-11-29T00:16:08 | ---
dataset_info:
features:
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num_examples: 901
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dataset_size: 98254212.0
configs:
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data_files:
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rollstar/marcosantonio1 | rollstar | 2023-11-29T00:22:05Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-29T00:22:05Z | 2023-11-29T00:17:10.000Z | 2023-11-29T00:17:10 | ---
license: openrail
---
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