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decoy4600/sgm-output4
decoy4600
2023-11-28T06:23:16Z
0
0
null
[ "region:us" ]
2023-11-28T06:23:16Z
2023-11-28T06:22:50.000Z
2023-11-28T06:22:50
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
tolu07/Mental_Health_FAQ
tolu07
2023-11-28T06:33:34Z
0
0
null
[ "task_categories:conversational", "task_categories:text-generation", "license:mit", "chatbot", "mental health", "therapy", "region:us" ]
2023-11-28T06:33:34Z
2023-11-28T06:24:38.000Z
2023-11-28T06:24:38
--- license: mit task_categories: - conversational - text-generation tags: - chatbot - mental health - therapy --- **Content** Mental health includes our emotional, psychological, and social well-being. Mental health is integral to living a healthy, balanced life. It affects how we think, feel, and act. It also helps determine how we handle stress, relate to others, and make choices. Emotional and mental health is important because it’s a vital part of your life and impacts your thoughts, behaviors and emotions. Being healthy emotionally can promote productivity and effectiveness in activities like work, school or care-giving. It plays an important part in the health of your relationships, and allows you to adapt to changes in your life and cope with adversity. Mental health problems are common but help is available. People with mental health problems can get better and many recover completely. This dataset consists of FAQs about Mental Health. **Acknowledgements** https://www.thekimfoundation.org/faqs/ https://www.mhanational.org/frequently-asked-questions https://www.wellnessinmind.org/frequently-asked-questions/ https://www.heretohelp.bc.ca/questions-and-answers
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null
null
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adamjweintraut/eli5_lfqa_top_slice
adamjweintraut
2023-11-28T06:27:49Z
0
0
null
[ "region:us" ]
2023-11-28T06:27:49Z
2023-11-28T06:27:01.000Z
2023-11-28T06:27:01
--- dataset_info: features: - name: index dtype: int64 - name: q_id dtype: string - name: question dtype: string - name: best_answer dtype: string - name: all_answers sequence: string - name: num_answers dtype: int64 - name: top_answers sequence: string - name: num_top_answers dtype: int64 - name: context dtype: string - name: orig dtype: string - name: target dtype: string splits: - name: train num_bytes: 304163516 num_examples: 20000 - name: test num_bytes: 38395443 num_examples: 2500 - name: validation num_bytes: 39481266 num_examples: 2500 download_size: 229456929 dataset_size: 382040225 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: validation path: data/validation-* ---
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roupenminassian/vehicle-dataset-v2
roupenminassian
2023-11-28T06:36:20Z
0
0
null
[ "region:us" ]
2023-11-28T06:36:20Z
2023-11-28T06:35:21.000Z
2023-11-28T06:35:21
--- 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: int64 splits: - name: train num_bytes: 120781140.624 num_examples: 1128 download_size: 122076069 dataset_size: 120781140.624 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "vehicle-dataset-v2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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sam-mosaic/iv4-chatml-8k
sam-mosaic
2023-11-28T06:38:55Z
0
0
null
[ "region:us" ]
2023-11-28T06:38:55Z
2023-11-28T06:37:50.000Z
2023-11-28T06:37:50
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: source dtype: string - name: prompt dtype: string - name: response dtype: string splits: - name: train num_bytes: 2207667895.4360986 num_examples: 363958 - name: test num_bytes: 330419382.2206894 num_examples: 54042 download_size: 618017532 dataset_size: 2538087277.656788 --- # Dataset Card for "iv4-chatml-8k" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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null
null
null
null
null
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sam-mosaic/iv4-chatml-4k
sam-mosaic
2023-11-28T07:03:55Z
0
0
null
[ "region:us" ]
2023-11-28T07:03:55Z
2023-11-28T06:39:31.000Z
2023-11-28T06:39:31
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: source dtype: string - name: prompt dtype: string - name: response dtype: string splits: - name: train num_bytes: 2099655591.2305844 num_examples: 346151 - name: test num_bytes: 315348071.4406665 num_examples: 51577 download_size: 295209643 dataset_size: 2415003662.671251 --- # Dataset Card for "iv4-chatml-4k" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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null
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null
null
null
null
null
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sam-mosaic/iv4-chatml-16k
sam-mosaic
2023-11-28T06:43:19Z
0
0
null
[ "region:us" ]
2023-11-28T06:43:19Z
2023-11-28T06:41:35.000Z
2023-11-28T06:41:35
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: source dtype: string - name: prompt dtype: string - name: response dtype: string splits: - name: train num_bytes: 2334144256.136339 num_examples: 384809 - name: test num_bytes: 349214193.311071 num_examples: 57116 download_size: 1227729872 dataset_size: 2683358449.44741 --- # Dataset Card for "iv4-chatml-16k" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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null
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X2FD/LVIS-Instruct4V-LLaVA-Instruct-mix880k
X2FD
2023-11-28T06:53:07Z
0
0
null
[ "region:us" ]
2023-11-28T06:53:07Z
2023-11-28T06:43:55.000Z
2023-11-28T06:43:55
# LVIS-Instruct4V-LLaVA-Instruct-mix880k This is a mixture of our LVIS-Instruct4V dataset with [LLaVA-Instruct](https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K/blob/main/llava_instruct_150k.json) (150k) , and the academic task related data, including ShareGPT, VQAv2, GQA, OKVQA, OCRVQA, AOKVQA, TextCaps, RefCOCO, and VG.
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Xiami2000/Trainingforaxolotl
Xiami2000
2023-11-28T15:43:28Z
0
0
null
[ "region:us" ]
2023-11-28T15:43:28Z
2023-11-28T06:48:21.000Z
2023-11-28T06:48:21
整理好的一些H小说jsonl文件
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roupenminassian/vehicle-dataset-v3
roupenminassian
2023-11-28T06:52:32Z
0
0
null
[ "region:us" ]
2023-11-28T06:52:32Z
2023-11-28T06:51:28.000Z
2023-11-28T06:51:28
--- 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: int64 splits: - name: train num_bytes: 120781140.624 num_examples: 1128 download_size: 122076069 dataset_size: 120781140.624 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "vehicle-dataset-v3" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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swulling/gsm8k_chinese
swulling
2023-11-28T08:48:01Z
0
1
null
[ "task_categories:text2text-generation", "size_categories:1K<n<10K", "source_datasets:gsm8k", "language:zh", "license:mit", "math-word-problems", "region:us" ]
2023-11-28T08:48:01Z
2023-11-28T06:53:43.000Z
2023-11-28T06:53:43
--- language: - zh license: mit size_categories: - 1K<n<10K source_datasets: - gsm8k task_categories: - text2text-generation dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: question_zh-cn dtype: string - name: answer_only dtype: int64 splits: - name: test num_bytes: 1020788 num_examples: 1319 - name: train num_bytes: 5664657 num_examples: 7473 download_size: 3988161 dataset_size: 6685445 configs: - config_name: default data_files: - split: test path: data/test-* - split: train path: data/train-* tags: - math-word-problems ---
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diffusers/pokemon-gpt4-captions
diffusers
2023-11-28T07:07:09Z
0
2
null
[ "task_categories:text-to-image", "size_categories:1K<n<10K", "language:en", "license:other", "region:us" ]
2023-11-28T07:07:09Z
2023-11-28T06:54:16.000Z
2023-11-28T06:54:16
--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 56664550 num_examples: 833 download_size: 51051224 dataset_size: 56664550 configs: - config_name: default data_files: - split: train path: data/train-* license: other task_categories: - text-to-image language: - en pretty_name: 'Pokemons with captions generated using GPT-4. ' size_categories: - 1K<n<10K --- # Dataset Card for "pokemon-gpt4-captions" This dataset is just [lambdalabs/pokemon-blip-captions](https://huggingface.co/datasets/lambdalabs/pokemon-blip-captions) but the captions come from GPT-4 (Turbo). Code used to generate the captions: ```python import base64 from io import BytesIO import requests from PIL import Image def encode_image(image): buffered = BytesIO() image.save(buffered, format="JPEG") img_str = base64.b64encode(buffered.getvalue()) return img_str.decode("utf-8") def create_payload(image_string): payload = { "model": "gpt-4-vision-preview", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Provide caption for the image in one sentence. Be detailed but precise.", }, { "type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{image_string}"}, }, ], } ], "max_tokens": 100, } return payload def get_response(image_string): payload = create_payload(image_string) response = requests.post( "https://api.openai.com/v1/chat/completions", headers=headers, json=payload ) return response.json() image = Image.open("path_to_you_image").convert("RGB") image_str = encode_image(image) response = get_response(image_str) ``` Generating captions for 833 images from the [lambdalabs/pokemon-blip-captions](https://huggingface.co/datasets/lambdalabs/pokemon-blip-captions) dataset costed about $5. You can use this dataset for non-commercial applications.
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Imran1/newdatasetdogb
Imran1
2023-11-28T06:58:11Z
0
0
null
[ "region:us" ]
2023-11-28T06:58:11Z
2023-11-28T06:58:04.000Z
2023-11-28T06:58:04
--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': Australian_shepherd '1': Chihuahua '2': French_bulldog splits: - name: train num_bytes: 79657324.7834681 num_examples: 3363 download_size: 76864604 dataset_size: 79657324.7834681 configs: - config_name: default data_files: - split: train path: data/train-* ---
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BroJack/alpaca_lora_training_dataset
BroJack
2023-11-28T07:00:49Z
0
0
null
[ "region:us" ]
2023-11-28T07:00:49Z
2023-11-28T06:59:47.000Z
2023-11-28T06:59:47
Entry not found
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BangumiBase/deathparade
BangumiBase
2023-11-28T08:41:17Z
0
0
null
[ "size_categories:1K<n<10K", "license:mit", "art", "region:us" ]
2023-11-28T08:41:17Z
2023-11-28T07:01:59.000Z
2023-11-28T07:01:59
--- license: mit tags: - art size_categories: - 1K<n<10K --- # Bangumi Image Base of Death Parade This is the image base of bangumi Death Parade, we detected 20 characters, 1332 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 | 186 | [Download](0/dataset.zip) | ![preview 1](0/preview_1.png) | ![preview 2](0/preview_2.png) | ![preview 3](0/preview_3.png) | ![preview 4](0/preview_4.png) | ![preview 5](0/preview_5.png) | ![preview 6](0/preview_6.png) | ![preview 7](0/preview_7.png) | ![preview 8](0/preview_8.png) | | 1 | 28 | [Download](1/dataset.zip) | ![preview 1](1/preview_1.png) | ![preview 2](1/preview_2.png) | ![preview 3](1/preview_3.png) | ![preview 4](1/preview_4.png) | ![preview 5](1/preview_5.png) | ![preview 6](1/preview_6.png) | ![preview 7](1/preview_7.png) | ![preview 8](1/preview_8.png) | | 2 | 57 | [Download](2/dataset.zip) | ![preview 1](2/preview_1.png) | ![preview 2](2/preview_2.png) | ![preview 3](2/preview_3.png) | ![preview 4](2/preview_4.png) | ![preview 5](2/preview_5.png) | ![preview 6](2/preview_6.png) | ![preview 7](2/preview_7.png) | ![preview 8](2/preview_8.png) | | 3 | 45 | [Download](3/dataset.zip) | ![preview 1](3/preview_1.png) | ![preview 2](3/preview_2.png) | ![preview 3](3/preview_3.png) | ![preview 4](3/preview_4.png) | ![preview 5](3/preview_5.png) | ![preview 6](3/preview_6.png) | ![preview 7](3/preview_7.png) | ![preview 8](3/preview_8.png) | | 4 | 59 | [Download](4/dataset.zip) | ![preview 1](4/preview_1.png) | ![preview 2](4/preview_2.png) | ![preview 3](4/preview_3.png) | ![preview 4](4/preview_4.png) | ![preview 5](4/preview_5.png) | ![preview 6](4/preview_6.png) | ![preview 7](4/preview_7.png) | ![preview 8](4/preview_8.png) | | 5 | 70 | [Download](5/dataset.zip) | ![preview 1](5/preview_1.png) | ![preview 2](5/preview_2.png) | ![preview 3](5/preview_3.png) | ![preview 4](5/preview_4.png) | ![preview 5](5/preview_5.png) | ![preview 6](5/preview_6.png) | ![preview 7](5/preview_7.png) | ![preview 8](5/preview_8.png) | | 6 | 31 | [Download](6/dataset.zip) | ![preview 1](6/preview_1.png) | ![preview 2](6/preview_2.png) | ![preview 3](6/preview_3.png) | ![preview 4](6/preview_4.png) | ![preview 5](6/preview_5.png) | ![preview 6](6/preview_6.png) | ![preview 7](6/preview_7.png) | ![preview 8](6/preview_8.png) | | 7 | 72 | [Download](7/dataset.zip) | ![preview 1](7/preview_1.png) | ![preview 2](7/preview_2.png) | ![preview 3](7/preview_3.png) | ![preview 4](7/preview_4.png) | ![preview 5](7/preview_5.png) | ![preview 6](7/preview_6.png) | ![preview 7](7/preview_7.png) | ![preview 8](7/preview_8.png) | | 8 | 117 | [Download](8/dataset.zip) | ![preview 1](8/preview_1.png) | ![preview 2](8/preview_2.png) | ![preview 3](8/preview_3.png) | ![preview 4](8/preview_4.png) | ![preview 5](8/preview_5.png) | ![preview 6](8/preview_6.png) | ![preview 7](8/preview_7.png) | ![preview 8](8/preview_8.png) | | 9 | 46 | [Download](9/dataset.zip) | ![preview 1](9/preview_1.png) | ![preview 2](9/preview_2.png) | ![preview 3](9/preview_3.png) | ![preview 4](9/preview_4.png) | ![preview 5](9/preview_5.png) | ![preview 6](9/preview_6.png) | ![preview 7](9/preview_7.png) | ![preview 8](9/preview_8.png) | | 10 | 40 | [Download](10/dataset.zip) | ![preview 1](10/preview_1.png) | ![preview 2](10/preview_2.png) | ![preview 3](10/preview_3.png) | ![preview 4](10/preview_4.png) | ![preview 5](10/preview_5.png) | ![preview 6](10/preview_6.png) | ![preview 7](10/preview_7.png) | ![preview 8](10/preview_8.png) | | 11 | 63 | [Download](11/dataset.zip) | ![preview 1](11/preview_1.png) | ![preview 2](11/preview_2.png) | ![preview 3](11/preview_3.png) | ![preview 4](11/preview_4.png) | ![preview 5](11/preview_5.png) | ![preview 6](11/preview_6.png) | ![preview 7](11/preview_7.png) | ![preview 8](11/preview_8.png) | | 12 | 15 | [Download](12/dataset.zip) | ![preview 1](12/preview_1.png) | ![preview 2](12/preview_2.png) | ![preview 3](12/preview_3.png) | ![preview 4](12/preview_4.png) | ![preview 5](12/preview_5.png) | ![preview 6](12/preview_6.png) | ![preview 7](12/preview_7.png) | ![preview 8](12/preview_8.png) | | 13 | 22 | [Download](13/dataset.zip) | ![preview 1](13/preview_1.png) | ![preview 2](13/preview_2.png) | ![preview 3](13/preview_3.png) | ![preview 4](13/preview_4.png) | ![preview 5](13/preview_5.png) | ![preview 6](13/preview_6.png) | ![preview 7](13/preview_7.png) | ![preview 8](13/preview_8.png) | | 14 | 214 | [Download](14/dataset.zip) | ![preview 1](14/preview_1.png) | ![preview 2](14/preview_2.png) | ![preview 3](14/preview_3.png) | ![preview 4](14/preview_4.png) | ![preview 5](14/preview_5.png) | ![preview 6](14/preview_6.png) | ![preview 7](14/preview_7.png) | ![preview 8](14/preview_8.png) | | 15 | 60 | [Download](15/dataset.zip) | ![preview 1](15/preview_1.png) | ![preview 2](15/preview_2.png) | ![preview 3](15/preview_3.png) | ![preview 4](15/preview_4.png) | ![preview 5](15/preview_5.png) | ![preview 6](15/preview_6.png) | ![preview 7](15/preview_7.png) | ![preview 8](15/preview_8.png) | | 16 | 49 | [Download](16/dataset.zip) | ![preview 1](16/preview_1.png) | ![preview 2](16/preview_2.png) | ![preview 3](16/preview_3.png) | ![preview 4](16/preview_4.png) | ![preview 5](16/preview_5.png) | ![preview 6](16/preview_6.png) | ![preview 7](16/preview_7.png) | ![preview 8](16/preview_8.png) | | 17 | 13 | [Download](17/dataset.zip) | ![preview 1](17/preview_1.png) | ![preview 2](17/preview_2.png) | ![preview 3](17/preview_3.png) | ![preview 4](17/preview_4.png) | ![preview 5](17/preview_5.png) | ![preview 6](17/preview_6.png) | ![preview 7](17/preview_7.png) | ![preview 8](17/preview_8.png) | | 18 | 47 | [Download](18/dataset.zip) | ![preview 1](18/preview_1.png) | ![preview 2](18/preview_2.png) | ![preview 3](18/preview_3.png) | ![preview 4](18/preview_4.png) | ![preview 5](18/preview_5.png) | ![preview 6](18/preview_6.png) | ![preview 7](18/preview_7.png) | ![preview 8](18/preview_8.png) | | noise | 98 | [Download](-1/dataset.zip) | ![preview 1](-1/preview_1.png) | ![preview 2](-1/preview_2.png) | ![preview 3](-1/preview_3.png) | ![preview 4](-1/preview_4.png) | ![preview 5](-1/preview_5.png) | ![preview 6](-1/preview_6.png) | ![preview 7](-1/preview_7.png) | ![preview 8](-1/preview_8.png) |
[ -0.6984877586364746, -0.1498137265443802, 0.14263057708740234, 0.22603841125965118, -0.28747469186782837, -0.017097553238272667, 0.0008750214474275708, -0.3377918303012848, 0.6570323705673218, 0.5274203419685364, -0.9289644956588745, -0.8810428977012634, -0.6655895113945007, 0.453676223754...
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BangumiBase/ariatheanimation
BangumiBase
2023-11-28T10:55:37Z
0
0
null
[ "size_categories:1K<n<10K", "license:mit", "art", "region:us" ]
2023-11-28T10:55:37Z
2023-11-28T07:03:51.000Z
2023-11-28T07:03:51
--- license: mit tags: - art size_categories: - 1K<n<10K --- # Bangumi Image Base of Aria The Animation This is the image base of bangumi Aria The Animation, we detected 50 characters, 5059 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 | 1592 | [Download](0/dataset.zip) | ![preview 1](0/preview_1.png) | ![preview 2](0/preview_2.png) | ![preview 3](0/preview_3.png) | ![preview 4](0/preview_4.png) | ![preview 5](0/preview_5.png) | ![preview 6](0/preview_6.png) | ![preview 7](0/preview_7.png) | ![preview 8](0/preview_8.png) | | 1 | 18 | [Download](1/dataset.zip) | ![preview 1](1/preview_1.png) | ![preview 2](1/preview_2.png) | ![preview 3](1/preview_3.png) | ![preview 4](1/preview_4.png) | ![preview 5](1/preview_5.png) | ![preview 6](1/preview_6.png) | ![preview 7](1/preview_7.png) | ![preview 8](1/preview_8.png) | | 2 | 29 | [Download](2/dataset.zip) | ![preview 1](2/preview_1.png) | ![preview 2](2/preview_2.png) | ![preview 3](2/preview_3.png) | ![preview 4](2/preview_4.png) | ![preview 5](2/preview_5.png) | ![preview 6](2/preview_6.png) | ![preview 7](2/preview_7.png) | ![preview 8](2/preview_8.png) | | 3 | 25 | [Download](3/dataset.zip) | ![preview 1](3/preview_1.png) | ![preview 2](3/preview_2.png) | ![preview 3](3/preview_3.png) | ![preview 4](3/preview_4.png) | ![preview 5](3/preview_5.png) | ![preview 6](3/preview_6.png) | ![preview 7](3/preview_7.png) | ![preview 8](3/preview_8.png) | | 4 | 20 | [Download](4/dataset.zip) | ![preview 1](4/preview_1.png) | ![preview 2](4/preview_2.png) | ![preview 3](4/preview_3.png) | ![preview 4](4/preview_4.png) | ![preview 5](4/preview_5.png) | ![preview 6](4/preview_6.png) | ![preview 7](4/preview_7.png) | ![preview 8](4/preview_8.png) | | 5 | 22 | [Download](5/dataset.zip) | ![preview 1](5/preview_1.png) | ![preview 2](5/preview_2.png) | ![preview 3](5/preview_3.png) | ![preview 4](5/preview_4.png) | ![preview 5](5/preview_5.png) | ![preview 6](5/preview_6.png) | ![preview 7](5/preview_7.png) | ![preview 8](5/preview_8.png) | | 6 | 30 | [Download](6/dataset.zip) | ![preview 1](6/preview_1.png) | ![preview 2](6/preview_2.png) | ![preview 3](6/preview_3.png) | ![preview 4](6/preview_4.png) | ![preview 5](6/preview_5.png) | ![preview 6](6/preview_6.png) | ![preview 7](6/preview_7.png) | ![preview 8](6/preview_8.png) | | 7 | 19 | [Download](7/dataset.zip) | ![preview 1](7/preview_1.png) | ![preview 2](7/preview_2.png) | ![preview 3](7/preview_3.png) | ![preview 4](7/preview_4.png) | ![preview 5](7/preview_5.png) | ![preview 6](7/preview_6.png) | ![preview 7](7/preview_7.png) | ![preview 8](7/preview_8.png) | | 8 | 42 | [Download](8/dataset.zip) | ![preview 1](8/preview_1.png) | ![preview 2](8/preview_2.png) | ![preview 3](8/preview_3.png) | ![preview 4](8/preview_4.png) | ![preview 5](8/preview_5.png) | ![preview 6](8/preview_6.png) | ![preview 7](8/preview_7.png) | ![preview 8](8/preview_8.png) | | 9 | 58 | [Download](9/dataset.zip) | ![preview 1](9/preview_1.png) | ![preview 2](9/preview_2.png) | ![preview 3](9/preview_3.png) | ![preview 4](9/preview_4.png) | ![preview 5](9/preview_5.png) | ![preview 6](9/preview_6.png) | ![preview 7](9/preview_7.png) | ![preview 8](9/preview_8.png) | | 10 | 58 | [Download](10/dataset.zip) | ![preview 1](10/preview_1.png) | ![preview 2](10/preview_2.png) | ![preview 3](10/preview_3.png) | ![preview 4](10/preview_4.png) | ![preview 5](10/preview_5.png) | ![preview 6](10/preview_6.png) | ![preview 7](10/preview_7.png) | ![preview 8](10/preview_8.png) | | 11 | 27 | [Download](11/dataset.zip) | ![preview 1](11/preview_1.png) | ![preview 2](11/preview_2.png) | ![preview 3](11/preview_3.png) | ![preview 4](11/preview_4.png) | ![preview 5](11/preview_5.png) | ![preview 6](11/preview_6.png) | ![preview 7](11/preview_7.png) | ![preview 8](11/preview_8.png) | | 12 | 22 | [Download](12/dataset.zip) | ![preview 1](12/preview_1.png) | ![preview 2](12/preview_2.png) | ![preview 3](12/preview_3.png) | ![preview 4](12/preview_4.png) | ![preview 5](12/preview_5.png) | ![preview 6](12/preview_6.png) | ![preview 7](12/preview_7.png) | ![preview 8](12/preview_8.png) | | 13 | 48 | [Download](13/dataset.zip) | ![preview 1](13/preview_1.png) | ![preview 2](13/preview_2.png) | ![preview 3](13/preview_3.png) | ![preview 4](13/preview_4.png) | ![preview 5](13/preview_5.png) | ![preview 6](13/preview_6.png) | ![preview 7](13/preview_7.png) | ![preview 8](13/preview_8.png) | | 14 | 106 | [Download](14/dataset.zip) | ![preview 1](14/preview_1.png) | ![preview 2](14/preview_2.png) | ![preview 3](14/preview_3.png) | ![preview 4](14/preview_4.png) | ![preview 5](14/preview_5.png) | ![preview 6](14/preview_6.png) | ![preview 7](14/preview_7.png) | ![preview 8](14/preview_8.png) | | 15 | 15 | [Download](15/dataset.zip) | ![preview 1](15/preview_1.png) | ![preview 2](15/preview_2.png) | ![preview 3](15/preview_3.png) | ![preview 4](15/preview_4.png) | ![preview 5](15/preview_5.png) | ![preview 6](15/preview_6.png) | ![preview 7](15/preview_7.png) | ![preview 8](15/preview_8.png) | | 16 | 18 | [Download](16/dataset.zip) | ![preview 1](16/preview_1.png) | ![preview 2](16/preview_2.png) | ![preview 3](16/preview_3.png) | ![preview 4](16/preview_4.png) | ![preview 5](16/preview_5.png) | ![preview 6](16/preview_6.png) | ![preview 7](16/preview_7.png) | ![preview 8](16/preview_8.png) | | 17 | 87 | [Download](17/dataset.zip) | ![preview 1](17/preview_1.png) | ![preview 2](17/preview_2.png) | ![preview 3](17/preview_3.png) | ![preview 4](17/preview_4.png) | ![preview 5](17/preview_5.png) | ![preview 6](17/preview_6.png) | ![preview 7](17/preview_7.png) | ![preview 8](17/preview_8.png) | | 18 | 25 | [Download](18/dataset.zip) | ![preview 1](18/preview_1.png) | ![preview 2](18/preview_2.png) | ![preview 3](18/preview_3.png) | ![preview 4](18/preview_4.png) | ![preview 5](18/preview_5.png) | ![preview 6](18/preview_6.png) | ![preview 7](18/preview_7.png) | ![preview 8](18/preview_8.png) | | 19 | 26 | [Download](19/dataset.zip) | ![preview 1](19/preview_1.png) | ![preview 2](19/preview_2.png) | ![preview 3](19/preview_3.png) | ![preview 4](19/preview_4.png) | ![preview 5](19/preview_5.png) | ![preview 6](19/preview_6.png) | ![preview 7](19/preview_7.png) | ![preview 8](19/preview_8.png) | | 20 | 13 | [Download](20/dataset.zip) | ![preview 1](20/preview_1.png) | ![preview 2](20/preview_2.png) | ![preview 3](20/preview_3.png) | ![preview 4](20/preview_4.png) | ![preview 5](20/preview_5.png) | ![preview 6](20/preview_6.png) | ![preview 7](20/preview_7.png) | ![preview 8](20/preview_8.png) | | 21 | 41 | [Download](21/dataset.zip) | ![preview 1](21/preview_1.png) | ![preview 2](21/preview_2.png) | ![preview 3](21/preview_3.png) | ![preview 4](21/preview_4.png) | ![preview 5](21/preview_5.png) | ![preview 6](21/preview_6.png) | ![preview 7](21/preview_7.png) | ![preview 8](21/preview_8.png) | | 22 | 183 | [Download](22/dataset.zip) | ![preview 1](22/preview_1.png) | ![preview 2](22/preview_2.png) | ![preview 3](22/preview_3.png) | ![preview 4](22/preview_4.png) | ![preview 5](22/preview_5.png) | ![preview 6](22/preview_6.png) | ![preview 7](22/preview_7.png) | ![preview 8](22/preview_8.png) | | 23 | 43 | [Download](23/dataset.zip) | ![preview 1](23/preview_1.png) | ![preview 2](23/preview_2.png) | ![preview 3](23/preview_3.png) | ![preview 4](23/preview_4.png) | ![preview 5](23/preview_5.png) | ![preview 6](23/preview_6.png) | ![preview 7](23/preview_7.png) | ![preview 8](23/preview_8.png) | | 24 | 387 | [Download](24/dataset.zip) | ![preview 1](24/preview_1.png) | ![preview 2](24/preview_2.png) | ![preview 3](24/preview_3.png) | ![preview 4](24/preview_4.png) | ![preview 5](24/preview_5.png) | ![preview 6](24/preview_6.png) | ![preview 7](24/preview_7.png) | ![preview 8](24/preview_8.png) | | 25 | 336 | [Download](25/dataset.zip) | ![preview 1](25/preview_1.png) | ![preview 2](25/preview_2.png) | ![preview 3](25/preview_3.png) | ![preview 4](25/preview_4.png) | ![preview 5](25/preview_5.png) | ![preview 6](25/preview_6.png) | ![preview 7](25/preview_7.png) | ![preview 8](25/preview_8.png) | | 26 | 30 | [Download](26/dataset.zip) | ![preview 1](26/preview_1.png) | ![preview 2](26/preview_2.png) | ![preview 3](26/preview_3.png) | ![preview 4](26/preview_4.png) | ![preview 5](26/preview_5.png) | ![preview 6](26/preview_6.png) | ![preview 7](26/preview_7.png) | ![preview 8](26/preview_8.png) | | 27 | 12 | [Download](27/dataset.zip) | ![preview 1](27/preview_1.png) | ![preview 2](27/preview_2.png) | ![preview 3](27/preview_3.png) | ![preview 4](27/preview_4.png) | ![preview 5](27/preview_5.png) | ![preview 6](27/preview_6.png) | ![preview 7](27/preview_7.png) | ![preview 8](27/preview_8.png) | | 28 | 34 | [Download](28/dataset.zip) | ![preview 1](28/preview_1.png) | ![preview 2](28/preview_2.png) | ![preview 3](28/preview_3.png) | ![preview 4](28/preview_4.png) | ![preview 5](28/preview_5.png) | ![preview 6](28/preview_6.png) | ![preview 7](28/preview_7.png) | ![preview 8](28/preview_8.png) | | 29 | 18 | [Download](29/dataset.zip) | ![preview 1](29/preview_1.png) | ![preview 2](29/preview_2.png) | ![preview 3](29/preview_3.png) | ![preview 4](29/preview_4.png) | ![preview 5](29/preview_5.png) | ![preview 6](29/preview_6.png) | ![preview 7](29/preview_7.png) | ![preview 8](29/preview_8.png) | | 30 | 106 | [Download](30/dataset.zip) | ![preview 1](30/preview_1.png) | ![preview 2](30/preview_2.png) | ![preview 3](30/preview_3.png) | ![preview 4](30/preview_4.png) | ![preview 5](30/preview_5.png) | ![preview 6](30/preview_6.png) | ![preview 7](30/preview_7.png) | ![preview 8](30/preview_8.png) | | 31 | 26 | [Download](31/dataset.zip) | ![preview 1](31/preview_1.png) | ![preview 2](31/preview_2.png) | ![preview 3](31/preview_3.png) | ![preview 4](31/preview_4.png) | ![preview 5](31/preview_5.png) | ![preview 6](31/preview_6.png) | ![preview 7](31/preview_7.png) | ![preview 8](31/preview_8.png) | | 32 | 7 | [Download](32/dataset.zip) | ![preview 1](32/preview_1.png) | ![preview 2](32/preview_2.png) | ![preview 3](32/preview_3.png) | ![preview 4](32/preview_4.png) | ![preview 5](32/preview_5.png) | ![preview 6](32/preview_6.png) | ![preview 7](32/preview_7.png) | N/A | | 33 | 19 | [Download](33/dataset.zip) | ![preview 1](33/preview_1.png) | ![preview 2](33/preview_2.png) | ![preview 3](33/preview_3.png) | ![preview 4](33/preview_4.png) | ![preview 5](33/preview_5.png) | ![preview 6](33/preview_6.png) | ![preview 7](33/preview_7.png) | ![preview 8](33/preview_8.png) | | 34 | 488 | [Download](34/dataset.zip) | ![preview 1](34/preview_1.png) | ![preview 2](34/preview_2.png) | ![preview 3](34/preview_3.png) | ![preview 4](34/preview_4.png) | ![preview 5](34/preview_5.png) | ![preview 6](34/preview_6.png) | ![preview 7](34/preview_7.png) | ![preview 8](34/preview_8.png) | | 35 | 87 | [Download](35/dataset.zip) | ![preview 1](35/preview_1.png) | ![preview 2](35/preview_2.png) | ![preview 3](35/preview_3.png) | ![preview 4](35/preview_4.png) | ![preview 5](35/preview_5.png) | ![preview 6](35/preview_6.png) | ![preview 7](35/preview_7.png) | ![preview 8](35/preview_8.png) | | 36 | 19 | [Download](36/dataset.zip) | ![preview 1](36/preview_1.png) | ![preview 2](36/preview_2.png) | ![preview 3](36/preview_3.png) | ![preview 4](36/preview_4.png) | ![preview 5](36/preview_5.png) | ![preview 6](36/preview_6.png) | ![preview 7](36/preview_7.png) | ![preview 8](36/preview_8.png) | | 37 | 395 | [Download](37/dataset.zip) | ![preview 1](37/preview_1.png) | ![preview 2](37/preview_2.png) | ![preview 3](37/preview_3.png) | ![preview 4](37/preview_4.png) | ![preview 5](37/preview_5.png) | ![preview 6](37/preview_6.png) | ![preview 7](37/preview_7.png) | ![preview 8](37/preview_8.png) | | 38 | 46 | [Download](38/dataset.zip) | ![preview 1](38/preview_1.png) | ![preview 2](38/preview_2.png) | ![preview 3](38/preview_3.png) | ![preview 4](38/preview_4.png) | ![preview 5](38/preview_5.png) | ![preview 6](38/preview_6.png) | ![preview 7](38/preview_7.png) | ![preview 8](38/preview_8.png) | | 39 | 15 | [Download](39/dataset.zip) | ![preview 1](39/preview_1.png) | ![preview 2](39/preview_2.png) | ![preview 3](39/preview_3.png) | ![preview 4](39/preview_4.png) | ![preview 5](39/preview_5.png) | ![preview 6](39/preview_6.png) | ![preview 7](39/preview_7.png) | ![preview 8](39/preview_8.png) | | 40 | 17 | [Download](40/dataset.zip) | ![preview 1](40/preview_1.png) | ![preview 2](40/preview_2.png) | ![preview 3](40/preview_3.png) | ![preview 4](40/preview_4.png) | ![preview 5](40/preview_5.png) | ![preview 6](40/preview_6.png) | ![preview 7](40/preview_7.png) | ![preview 8](40/preview_8.png) | | 41 | 24 | [Download](41/dataset.zip) | ![preview 1](41/preview_1.png) | ![preview 2](41/preview_2.png) | ![preview 3](41/preview_3.png) | ![preview 4](41/preview_4.png) | ![preview 5](41/preview_5.png) | ![preview 6](41/preview_6.png) | ![preview 7](41/preview_7.png) | ![preview 8](41/preview_8.png) | | 42 | 7 | [Download](42/dataset.zip) | ![preview 1](42/preview_1.png) | ![preview 2](42/preview_2.png) | ![preview 3](42/preview_3.png) | ![preview 4](42/preview_4.png) | ![preview 5](42/preview_5.png) | ![preview 6](42/preview_6.png) | ![preview 7](42/preview_7.png) | N/A | | 43 | 13 | [Download](43/dataset.zip) | ![preview 1](43/preview_1.png) | ![preview 2](43/preview_2.png) | ![preview 3](43/preview_3.png) | ![preview 4](43/preview_4.png) | ![preview 5](43/preview_5.png) | ![preview 6](43/preview_6.png) | ![preview 7](43/preview_7.png) | ![preview 8](43/preview_8.png) | | 44 | 8 | [Download](44/dataset.zip) | ![preview 1](44/preview_1.png) | ![preview 2](44/preview_2.png) | ![preview 3](44/preview_3.png) | ![preview 4](44/preview_4.png) | ![preview 5](44/preview_5.png) | ![preview 6](44/preview_6.png) | ![preview 7](44/preview_7.png) | ![preview 8](44/preview_8.png) | | 45 | 133 | [Download](45/dataset.zip) | ![preview 1](45/preview_1.png) | ![preview 2](45/preview_2.png) | ![preview 3](45/preview_3.png) | ![preview 4](45/preview_4.png) | ![preview 5](45/preview_5.png) | ![preview 6](45/preview_6.png) | ![preview 7](45/preview_7.png) | ![preview 8](45/preview_8.png) | | 46 | 6 | [Download](46/dataset.zip) | ![preview 1](46/preview_1.png) | ![preview 2](46/preview_2.png) | ![preview 3](46/preview_3.png) | ![preview 4](46/preview_4.png) | ![preview 5](46/preview_5.png) | ![preview 6](46/preview_6.png) | N/A | N/A | | 47 | 15 | [Download](47/dataset.zip) | ![preview 1](47/preview_1.png) | ![preview 2](47/preview_2.png) | ![preview 3](47/preview_3.png) | ![preview 4](47/preview_4.png) | ![preview 5](47/preview_5.png) | ![preview 6](47/preview_6.png) | ![preview 7](47/preview_7.png) | ![preview 8](47/preview_8.png) | | 48 | 15 | [Download](48/dataset.zip) | ![preview 1](48/preview_1.png) | ![preview 2](48/preview_2.png) | ![preview 3](48/preview_3.png) | ![preview 4](48/preview_4.png) | ![preview 5](48/preview_5.png) | ![preview 6](48/preview_6.png) | ![preview 7](48/preview_7.png) | ![preview 8](48/preview_8.png) | | noise | 229 | [Download](-1/dataset.zip) | ![preview 1](-1/preview_1.png) | ![preview 2](-1/preview_2.png) | ![preview 3](-1/preview_3.png) | ![preview 4](-1/preview_4.png) | ![preview 5](-1/preview_5.png) | ![preview 6](-1/preview_6.png) | ![preview 7](-1/preview_7.png) | ![preview 8](-1/preview_8.png) |
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null
null
null
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tarudesu/ViOCD
tarudesu
2023-11-28T07:19:05Z
0
0
null
[ "task_categories:text-classification", "size_categories:1K<n<10K", "language:vi", "code", "arxiv:2103.10069", "arxiv:2104.11969", "region:us" ]
2023-11-28T07:19:05Z
2023-11-28T07:13:26.000Z
2023-11-28T07:13:26
--- task_categories: - text-classification language: - vi tags: - code pretty_name: Vietnamese Open-Domain Complaint Detection in E-commerce Websites size_categories: - 1K<n<10K --- # Vietnamese Open-Domain Complaint Detection in E-commerce Websites This is the official repository for the UIT-ViCTSD dataset from the paper [Vietnamese Open-Domain Complaint Detection in E-commerce Websites](https://arxiv.org/pdf/2103.10069.pdf), which was accepted at the [SoMeT 2021](https://dblp.org/db/conf/somet/somet2021.html). # Citation Information The provided dataset is only used for research purposes! ``` @misc{nguyen2021vietnamese, title={Vietnamese Complaint Detection on E-Commerce Websites}, author={Nhung Thi-Hong Nguyen and Phuong Phan-Dieu Ha and Luan Thanh Nguyen and Kiet Van Nguyen and Ngan Luu-Thuy Nguyen}, year={2021}, eprint={2104.11969}, archivePrefix={arXiv}, primaryClass={cs.CL} } ``` ## Abstract Customer product reviews play a role in improving the quality of products and services for business organizations or their brands. Complaining is an attitude that expresses dissatisfaction with an event or a product not meeting customer expectations. In this paper, we build a Open-domain Complaint Detection dataset (UIT-ViOCD), including 5,485 human-annotated reviews on four categories about product reviews on e-commerce sites. After the data collection phase, we proceed to the annotation task and achieve the inter-annotator agreement Am of 87%. Then, we present an extensive methodology for the research purposes and achieve 92.16% by F1-score for identifying complaints. With the results, in the future, we aim to build a system for open-domain complaint detection in E-commerce websites. ## Dataset The ViOCD dataset is consist of 5,485 reviews on four categories about product reviews on e-commerce sites. The dataset is divided into three parts as below: 1. Train set: 4.39K reviews 2. Valid set: 548 reviews 3. Test set: 549 reviews ## Contact Please feel free to contact us by email luannt@uit.edu.vn if you have any further information!
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null
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null
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nateraw/samsum-llamafied
nateraw
2023-11-28T07:16:01Z
0
0
null
[ "region:us" ]
2023-11-28T07:16:01Z
2023-11-28T07:15:43.000Z
2023-11-28T07:15:43
Entry not found
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null
null
null
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tyzhu/ds1_try_lora_merge
tyzhu
2023-11-28T07:49:05Z
0
0
null
[ "region:us" ]
2023-11-28T07:49:05Z
2023-11-28T07:20:51.000Z
2023-11-28T07:20:51
--- dataset_info: features: - name: inputs dtype: string - name: targets dtype: string splits: - name: train num_bytes: 1044.247619047619 num_examples: 10 - name: validation num_bytes: 1044.247619047619 num_examples: 10 download_size: 4678 dataset_size: 2088.495238095238 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* --- # Dataset Card for "ds1_try_lora_merge" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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tyzhu/ds2_try_lora_merge
tyzhu
2023-11-28T07:49:26Z
0
0
null
[ "region:us" ]
2023-11-28T07:49:26Z
2023-11-28T07:21:16.000Z
2023-11-28T07:21:16
--- dataset_info: features: - name: inputs dtype: string - name: targets dtype: string splits: - name: train num_bytes: 1044.247619047619 num_examples: 10 - name: validation num_bytes: 1044.247619047619 num_examples: 10 download_size: 4650 dataset_size: 2088.495238095238 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* --- # Dataset Card for "ds2_try_lora_merge" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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null
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null
null
null
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null
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tyzhu/ds_combined_try_lora_merge
tyzhu
2023-11-28T07:50:02Z
0
0
null
[ "region:us" ]
2023-11-28T07:50:02Z
2023-11-28T07:21:23.000Z
2023-11-28T07:21:23
--- dataset_info: features: - name: inputs dtype: string - name: targets dtype: string splits: - name: train num_bytes: 2088.495238095238 num_examples: 20 - name: validation num_bytes: 2088.495238095238 num_examples: 20 download_size: 5988 dataset_size: 4176.990476190476 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* --- # Dataset Card for "ds_combined_try_lora_merge" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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cyy0/BMTL
cyy0
2023-11-28T07:22:23Z
0
0
null
[ "license:agpl-3.0", "region:us" ]
2023-11-28T07:22:23Z
2023-11-28T07:22:22.000Z
2023-11-28T07:22:22
--- license: agpl-3.0 ---
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null
null
null
null
null
null
null
null
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null
null
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Linata/test_dataset
Linata
2023-11-28T07:33:14Z
0
0
null
[ "license:mit", "region:us" ]
2023-11-28T07:33:14Z
2023-11-28T07:31:53.000Z
2023-11-28T07:31:53
--- license: mit ---
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null
null
null
null
null
null
null
null
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wesley7137/MMath14k
wesley7137
2023-11-28T07:33:25Z
0
0
null
[ "region:us" ]
2023-11-28T07:33:25Z
2023-11-28T07:33:11.000Z
2023-11-28T07:33:11
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
Stein-Fun/ddpm-butterflies-128
Stein-Fun
2023-11-28T07:33:53Z
0
0
null
[ "license:mit", "region:us" ]
2023-11-28T07:33:53Z
2023-11-28T07:33:51.000Z
2023-11-28T07:33:51
--- license: mit ---
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null
null
null
null
null
null
null
null
null
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edwinpalegre/trashnet_enhanced
edwinpalegre
2023-11-28T17:59:51Z
0
0
null
[ "region:us" ]
2023-11-28T17:59:51Z
2023-11-28T07:34:52.000Z
2023-11-28T07:34:52
--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': biodegradable '1': cardboard '2': glass '3': metal '4': paper '5': plastic '6': trash splits: - name: train num_bytes: 505205957.636 num_examples: 19892 download_size: 3977396925 dataset_size: 505205957.636 configs: - config_name: default data_files: - split: train path: data/train-* ---
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siddrao11/test
siddrao11
2023-11-28T08:06:11Z
0
0
null
[ "region:us" ]
2023-11-28T08:06:11Z
2023-11-28T07:38:42.000Z
2023-11-28T07:38:42
--- # For reference on dataset card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1 # Doc / guide: https://huggingface.co/docs/hub/datasets-cards {} --- # 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 <!-- Provide a longer summary of what this dataset is. --> - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- 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. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
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desarrolloasesoreslocales/MistralAI
desarrolloasesoreslocales
2023-11-28T08:00:28Z
0
0
null
[ "region:us" ]
2023-11-28T08:00:28Z
2023-11-28T07:43:14.000Z
2023-11-28T07:43:14
--- configs: - config_name: default data_files: - split: train path: data.csv --- # Dataset Card for Dataset Name <!-- Provide a quick summary of the dataset. --> ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- 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. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
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null
null
null
null
null
null
null
null
null
null
null
null
null
Mousaicv/gpt4_reward_train
Mousaicv
2023-11-28T07:50:09Z
0
0
null
[ "license:apache-2.0", "region:us" ]
2023-11-28T07:50:09Z
2023-11-28T07:48:14.000Z
2023-11-28T07:48:14
--- license: apache-2.0 ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
Imran1/dogbalance_data
Imran1
2023-11-28T08:05:12Z
0
0
null
[ "region:us" ]
2023-11-28T08:05:12Z
2023-11-28T08:05:04.000Z
2023-11-28T08:05:04
--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': Australian_shepherd '1': Chihuahua '2': French_bulldog splits: - name: train num_bytes: 18102241.0 num_examples: 735 download_size: 18093424 dataset_size: 18102241.0 configs: - config_name: default data_files: - split: train path: data/train-* ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
Docfile/Toi
Docfile
2023-11-28T08:13:55Z
0
0
null
[ "task_categories:translation", "language:fr", "license:apache-2.0", "legal", "region:us" ]
2023-11-28T08:13:55Z
2023-11-28T08:09:33.000Z
2023-11-28T08:09:33
--- license: apache-2.0 task_categories: - translation language: - fr tags: - legal ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
CHEN0312/fyefu
CHEN0312
2023-11-28T08:17:45Z
0
0
null
[ "license:apache-2.0", "region:us" ]
2023-11-28T08:17:45Z
2023-11-28T08:17:43.000Z
2023-11-28T08:17:43
--- license: apache-2.0 ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
rmatousek/ics
rmatousek
2023-11-28T08:21:02Z
0
0
null
[ "region:us" ]
2023-11-28T08:21:02Z
2023-11-28T08:17:55.000Z
2023-11-28T08:17:55
Entry not found
[ -0.3227647542953491, -0.22568407654762268, 0.8622258901596069, 0.4346148371696472, -0.5282984972000122, 0.7012965083122253, 0.7915717959403992, 0.07618629932403564, 0.7746022343635559, 0.2563222348690033, -0.785281777381897, -0.22573848068714142, -0.9104482531547546, 0.5715669393539429, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
tourist800/test
tourist800
2023-11-28T08:28:17Z
0
0
null
[ "license:mit", "region:us" ]
2023-11-28T08:28:17Z
2023-11-28T08:23:33.000Z
2023-11-28T08:23:33
--- license: mit ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
SUSTech/MetaMathQA
SUSTech
2023-11-28T11:28:02Z
0
0
null
[ "region:us" ]
2023-11-28T11:28:02Z
2023-11-28T08:23:43.000Z
2023-11-28T08:23:43
--- dataset_info: features: - name: response dtype: string - name: type dtype: string - name: query dtype: string splits: - name: train num_bytes: 286570703 num_examples: 395000 download_size: 140903789 dataset_size: 286570703 configs: - config_name: default data_files: - split: train path: data/train-* ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
zicsx/Hindi-YouTubeCC
zicsx
2023-11-28T08:48:07Z
0
0
null
[ "region:us" ]
2023-11-28T08:48:07Z
2023-11-28T08:27:42.000Z
2023-11-28T08:27:42
--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 6962453685 num_examples: 161248 download_size: 2554893278 dataset_size: 6962453685 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "Hindi-YouTubeCC" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.5777029991149902, -0.3458380103111267, -0.1282365769147873, 0.24914565682411194, -0.233870267868042, 0.24621081352233887, -0.05659063160419464, 0.18104737997055054, 0.8844714164733887, 0.12264534085988998, -0.8953933119773865, -0.6891379952430725, -0.8029922246932983, -0.191429853439331...
null
null
null
null
null
null
null
null
null
null
null
null
null
FrankFacundo/NaturalQuestionsMultilang
FrankFacundo
2023-11-28T09:34:05Z
0
0
null
[ "region:us" ]
2023-11-28T09:34:05Z
2023-11-28T08:30:30.000Z
2023-11-28T08:30:30
Entry not found
[ -0.32276472449302673, -0.22568407654762268, 0.8622258901596069, 0.4346148371696472, -0.5282984972000122, 0.7012965679168701, 0.7915717363357544, 0.07618629932403564, 0.7746022939682007, 0.2563222646713257, -0.785281777381897, -0.22573848068714142, -0.9104482531547546, 0.5715669393539429, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
sam1120/safety-utcustom-eval-v1.0
sam1120
2023-11-28T08:33:31Z
0
0
null
[ "region:us" ]
2023-11-28T08:33:31Z
2023-11-28T08:31:52.000Z
2023-11-28T08:31:52
--- dataset_info: features: - name: name dtype: string - name: pixel_values dtype: image - name: labels dtype: image splits: - name: train num_bytes: 139241854.0 num_examples: 50 download_size: 40367886 dataset_size: 139241854.0 --- # Dataset Card for "safety-utcustom-eval-50-v1.0" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.459087997674942, -0.21636013686656952, 0.17202800512313843, 0.33283260464668274, -0.2923942506313324, 0.11932279169559479, 0.20244646072387695, -0.2162804901599884, 0.6088123321533203, 0.478954941034317, -0.8197528123855591, -0.9340550899505615, -0.35364824533462524, -0.2645405530929565...
null
null
null
null
null
null
null
null
null
null
null
null
null
SUSTech/gsm8k-gpt35
SUSTech
2023-11-28T08:37:38Z
0
0
null
[ "region:us" ]
2023-11-28T08:37:38Z
2023-11-28T08:37:33.000Z
2023-11-28T08:37:33
--- dataset_info: features: - name: question dtype: string - name: answer dtype: string splits: - name: main num_bytes: 4355508 num_examples: 6840 - name: overlap num_bytes: 21003568 num_examples: 32825 download_size: 7092472 dataset_size: 25359076 configs: - config_name: default data_files: - split: main path: data/main-* - split: overlap path: data/overlap-* ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
euisuh15/python-piss-my-name-10
euisuh15
2023-11-28T08:43:43Z
0
0
null
[ "region:us" ]
2023-11-28T08:43:43Z
2023-11-28T08:41:34.000Z
2023-11-28T08:41:34
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
euisuh15/python-piss-my-name-30
euisuh15
2023-11-28T08:44:13Z
0
0
null
[ "region:us" ]
2023-11-28T08:44:13Z
2023-11-28T08:42:34.000Z
2023-11-28T08:42:34
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
euisuh15/python-piss-my-name-70
euisuh15
2023-11-28T08:46:30Z
0
0
null
[ "region:us" ]
2023-11-28T08:46:30Z
2023-11-28T08:44:33.000Z
2023-11-28T08:44:33
Entry not found
[ -0.3227649927139282, -0.225684255361557, 0.862226128578186, 0.43461498618125916, -0.5282987952232361, 0.7012963891029358, 0.7915717363357544, 0.07618629932403564, 0.7746025919914246, 0.2563219666481018, -0.7852816581726074, -0.2257382869720459, -0.9104480743408203, 0.5715669393539429, -0...
null
null
null
null
null
null
null
null
null
null
null
null
null
Wil16/essa
Wil16
2023-11-28T12:39:38Z
0
0
null
[ "region:us" ]
2023-11-28T12:39:38Z
2023-11-28T08:54:39.000Z
2023-11-28T08:54:39
Entry not found
[ -0.3227649927139282, -0.225684255361557, 0.862226128578186, 0.43461498618125916, -0.5282987952232361, 0.7012963891029358, 0.7915717363357544, 0.07618629932403564, 0.7746025919914246, 0.2563219666481018, -0.7852816581726074, -0.2257382869720459, -0.9104480743408203, 0.5715669393539429, -0...
null
null
null
null
null
null
null
null
null
null
null
null
null
Wauplin/dummy_gated_dataset
Wauplin
2023-11-28T09:02:59Z
0
0
null
[ "region:us" ]
2023-11-28T09:02:59Z
2023-11-28T09:02:59.000Z
2023-11-28T09:02:59
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
A2H0H0R1/alpaca_data_gpt4_2
A2H0H0R1
2023-11-28T09:07:19Z
0
0
null
[ "license:apache-2.0", "region:us" ]
2023-11-28T09:07:19Z
2023-11-28T09:06:35.000Z
2023-11-28T09:06:35
--- license: apache-2.0 ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
Andron00e/CIFAR10-custom
Andron00e
2023-11-28T09:43:03Z
0
0
null
[ "task_categories:image-classification", "size_categories:10K<n<100K", "language:en", "license:mit", "region:us" ]
2023-11-28T09:43:03Z
2023-11-28T09:20:50.000Z
2023-11-28T09:20:50
--- dataset_info: features: - name: image_file_path dtype: string - name: image dtype: image - name: labels dtype: uint8 splits: - name: train num_bytes: 59153400 num_examples: 60000 download_size: 26957572 dataset_size: 59153400 configs: - config_name: default data_files: - split: train path: data/train-* license: mit task_categories: - image-classification language: - en size_categories: - 10K<n<100K --- Example of usage: ```python from datasets import load_dataset dataset = load_dataset("Andron00e/CIFAR10-custom") splitted_dataset = dataset["train"].train_test_split(test_size=0.2) ```
[ -0.5458157062530518, -0.32690078020095825, -0.17638398706912994, 0.17882932722568512, -0.22993560135364532, -0.14087478816509247, 0.07836265116930008, 0.052019648253917694, 0.11030935496091843, 0.3083287179470062, -0.3192961812019348, 0.062392931431531906, -0.1426040530204773, 0.2852115333...
null
null
null
null
null
null
null
null
null
null
null
null
null
edzhu/binance_eth_bnb_btc_usdt_marketdata
edzhu
2023-11-28T09:27:50Z
0
0
null
[ "license:mit", "region:us" ]
2023-11-28T09:27:50Z
2023-11-28T09:21:53.000Z
2023-11-28T09:21:53
--- license: mit ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
Fissk/SG_dataset
Fissk
2023-11-28T09:36:30Z
0
0
null
[ "license:llama2", "region:us" ]
2023-11-28T09:36:30Z
2023-11-28T09:30:17.000Z
2023-11-28T09:30:17
--- license: llama2 ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
BangumiBase/princesstutu
BangumiBase
2023-11-28T11:12:28Z
0
0
null
[ "size_categories:1K<n<10K", "license:mit", "art", "region:us" ]
2023-11-28T11:12:28Z
2023-11-28T09:30:22.000Z
2023-11-28T09:30:22
--- license: mit tags: - art size_categories: - 1K<n<10K --- # Bangumi Image Base of Princess Tutu This is the image base of bangumi Princess Tutu, we detected 23 characters, 2179 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 | 190 | [Download](0/dataset.zip) | ![preview 1](0/preview_1.png) | ![preview 2](0/preview_2.png) | ![preview 3](0/preview_3.png) | ![preview 4](0/preview_4.png) | ![preview 5](0/preview_5.png) | ![preview 6](0/preview_6.png) | ![preview 7](0/preview_7.png) | ![preview 8](0/preview_8.png) | | 1 | 536 | [Download](1/dataset.zip) | ![preview 1](1/preview_1.png) | ![preview 2](1/preview_2.png) | ![preview 3](1/preview_3.png) | ![preview 4](1/preview_4.png) | ![preview 5](1/preview_5.png) | ![preview 6](1/preview_6.png) | ![preview 7](1/preview_7.png) | ![preview 8](1/preview_8.png) | | 2 | 67 | [Download](2/dataset.zip) | ![preview 1](2/preview_1.png) | ![preview 2](2/preview_2.png) | ![preview 3](2/preview_3.png) | ![preview 4](2/preview_4.png) | ![preview 5](2/preview_5.png) | ![preview 6](2/preview_6.png) | ![preview 7](2/preview_7.png) | ![preview 8](2/preview_8.png) | | 3 | 21 | [Download](3/dataset.zip) | ![preview 1](3/preview_1.png) | ![preview 2](3/preview_2.png) | ![preview 3](3/preview_3.png) | ![preview 4](3/preview_4.png) | ![preview 5](3/preview_5.png) | ![preview 6](3/preview_6.png) | ![preview 7](3/preview_7.png) | ![preview 8](3/preview_8.png) | | 4 | 288 | [Download](4/dataset.zip) | ![preview 1](4/preview_1.png) | ![preview 2](4/preview_2.png) | ![preview 3](4/preview_3.png) | ![preview 4](4/preview_4.png) | ![preview 5](4/preview_5.png) | ![preview 6](4/preview_6.png) | ![preview 7](4/preview_7.png) | ![preview 8](4/preview_8.png) | | 5 | 20 | [Download](5/dataset.zip) | ![preview 1](5/preview_1.png) | ![preview 2](5/preview_2.png) | ![preview 3](5/preview_3.png) | ![preview 4](5/preview_4.png) | ![preview 5](5/preview_5.png) | ![preview 6](5/preview_6.png) | ![preview 7](5/preview_7.png) | ![preview 8](5/preview_8.png) | | 6 | 19 | [Download](6/dataset.zip) | ![preview 1](6/preview_1.png) | ![preview 2](6/preview_2.png) | ![preview 3](6/preview_3.png) | ![preview 4](6/preview_4.png) | ![preview 5](6/preview_5.png) | ![preview 6](6/preview_6.png) | ![preview 7](6/preview_7.png) | ![preview 8](6/preview_8.png) | | 7 | 23 | [Download](7/dataset.zip) | ![preview 1](7/preview_1.png) | ![preview 2](7/preview_2.png) | ![preview 3](7/preview_3.png) | ![preview 4](7/preview_4.png) | ![preview 5](7/preview_5.png) | ![preview 6](7/preview_6.png) | ![preview 7](7/preview_7.png) | ![preview 8](7/preview_8.png) | | 8 | 22 | [Download](8/dataset.zip) | ![preview 1](8/preview_1.png) | ![preview 2](8/preview_2.png) | ![preview 3](8/preview_3.png) | ![preview 4](8/preview_4.png) | ![preview 5](8/preview_5.png) | ![preview 6](8/preview_6.png) | ![preview 7](8/preview_7.png) | ![preview 8](8/preview_8.png) | | 9 | 250 | [Download](9/dataset.zip) | ![preview 1](9/preview_1.png) | ![preview 2](9/preview_2.png) | ![preview 3](9/preview_3.png) | ![preview 4](9/preview_4.png) | ![preview 5](9/preview_5.png) | ![preview 6](9/preview_6.png) | ![preview 7](9/preview_7.png) | ![preview 8](9/preview_8.png) | | 10 | 352 | [Download](10/dataset.zip) | ![preview 1](10/preview_1.png) | ![preview 2](10/preview_2.png) | ![preview 3](10/preview_3.png) | ![preview 4](10/preview_4.png) | ![preview 5](10/preview_5.png) | ![preview 6](10/preview_6.png) | ![preview 7](10/preview_7.png) | ![preview 8](10/preview_8.png) | | 11 | 27 | [Download](11/dataset.zip) | ![preview 1](11/preview_1.png) | ![preview 2](11/preview_2.png) | ![preview 3](11/preview_3.png) | ![preview 4](11/preview_4.png) | ![preview 5](11/preview_5.png) | ![preview 6](11/preview_6.png) | ![preview 7](11/preview_7.png) | ![preview 8](11/preview_8.png) | | 12 | 23 | [Download](12/dataset.zip) | ![preview 1](12/preview_1.png) | ![preview 2](12/preview_2.png) | ![preview 3](12/preview_3.png) | ![preview 4](12/preview_4.png) | ![preview 5](12/preview_5.png) | ![preview 6](12/preview_6.png) | ![preview 7](12/preview_7.png) | ![preview 8](12/preview_8.png) | | 13 | 35 | [Download](13/dataset.zip) | ![preview 1](13/preview_1.png) | ![preview 2](13/preview_2.png) | ![preview 3](13/preview_3.png) | ![preview 4](13/preview_4.png) | ![preview 5](13/preview_5.png) | ![preview 6](13/preview_6.png) | ![preview 7](13/preview_7.png) | ![preview 8](13/preview_8.png) | | 14 | 22 | [Download](14/dataset.zip) | ![preview 1](14/preview_1.png) | ![preview 2](14/preview_2.png) | ![preview 3](14/preview_3.png) | ![preview 4](14/preview_4.png) | ![preview 5](14/preview_5.png) | ![preview 6](14/preview_6.png) | ![preview 7](14/preview_7.png) | ![preview 8](14/preview_8.png) | | 15 | 19 | [Download](15/dataset.zip) | ![preview 1](15/preview_1.png) | ![preview 2](15/preview_2.png) | ![preview 3](15/preview_3.png) | ![preview 4](15/preview_4.png) | ![preview 5](15/preview_5.png) | ![preview 6](15/preview_6.png) | ![preview 7](15/preview_7.png) | ![preview 8](15/preview_8.png) | | 16 | 38 | [Download](16/dataset.zip) | ![preview 1](16/preview_1.png) | ![preview 2](16/preview_2.png) | ![preview 3](16/preview_3.png) | ![preview 4](16/preview_4.png) | ![preview 5](16/preview_5.png) | ![preview 6](16/preview_6.png) | ![preview 7](16/preview_7.png) | ![preview 8](16/preview_8.png) | | 17 | 13 | [Download](17/dataset.zip) | ![preview 1](17/preview_1.png) | ![preview 2](17/preview_2.png) | ![preview 3](17/preview_3.png) | ![preview 4](17/preview_4.png) | ![preview 5](17/preview_5.png) | ![preview 6](17/preview_6.png) | ![preview 7](17/preview_7.png) | ![preview 8](17/preview_8.png) | | 18 | 10 | [Download](18/dataset.zip) | ![preview 1](18/preview_1.png) | ![preview 2](18/preview_2.png) | ![preview 3](18/preview_3.png) | ![preview 4](18/preview_4.png) | ![preview 5](18/preview_5.png) | ![preview 6](18/preview_6.png) | ![preview 7](18/preview_7.png) | ![preview 8](18/preview_8.png) | | 19 | 16 | [Download](19/dataset.zip) | ![preview 1](19/preview_1.png) | ![preview 2](19/preview_2.png) | ![preview 3](19/preview_3.png) | ![preview 4](19/preview_4.png) | ![preview 5](19/preview_5.png) | ![preview 6](19/preview_6.png) | ![preview 7](19/preview_7.png) | ![preview 8](19/preview_8.png) | | 20 | 67 | [Download](20/dataset.zip) | ![preview 1](20/preview_1.png) | ![preview 2](20/preview_2.png) | ![preview 3](20/preview_3.png) | ![preview 4](20/preview_4.png) | ![preview 5](20/preview_5.png) | ![preview 6](20/preview_6.png) | ![preview 7](20/preview_7.png) | ![preview 8](20/preview_8.png) | | 21 | 14 | [Download](21/dataset.zip) | ![preview 1](21/preview_1.png) | ![preview 2](21/preview_2.png) | ![preview 3](21/preview_3.png) | ![preview 4](21/preview_4.png) | ![preview 5](21/preview_5.png) | ![preview 6](21/preview_6.png) | ![preview 7](21/preview_7.png) | ![preview 8](21/preview_8.png) | | noise | 107 | [Download](-1/dataset.zip) | ![preview 1](-1/preview_1.png) | ![preview 2](-1/preview_2.png) | ![preview 3](-1/preview_3.png) | ![preview 4](-1/preview_4.png) | ![preview 5](-1/preview_5.png) | ![preview 6](-1/preview_6.png) | ![preview 7](-1/preview_7.png) | ![preview 8](-1/preview_8.png) |
[ -0.7046698331832886, -0.1679610311985016, 0.0711611658334732, 0.21716158092021942, -0.27490514516830444, -0.070058673620224, -0.03722704201936722, -0.34448471665382385, 0.6250349283218384, 0.49311959743499756, -0.9054293632507324, -0.8042576909065247, -0.6868444681167603, 0.539794445037841...
null
null
null
null
null
null
null
null
null
null
null
null
null
NobodyExistsOnTheInternet/sharegptairoboros
NobodyExistsOnTheInternet
2023-11-28T09:32:13Z
0
0
null
[ "license:mit", "region:us" ]
2023-11-28T09:32:13Z
2023-11-28T09:31:18.000Z
2023-11-28T09:31:18
--- license: mit ---
[ -0.1285335123538971, -0.1861683875322342, 0.6529128551483154, 0.49436232447624207, -0.19319400191307068, 0.23607441782951355, 0.36072009801864624, 0.05056373029947281, 0.5793656706809998, 0.7400146722793579, -0.650810182094574, -0.23784008622169495, -0.7102247476577759, -0.0478255338966846...
null
null
null
null
null
null
null
null
null
null
null
null
null
shenmixy/huggingface_token
shenmixy
2023-11-28T10:10:03Z
0
0
null
[ "region:us" ]
2023-11-28T10:10:03Z
2023-11-28T09:33:00.000Z
2023-11-28T09:33:00
cp -r -f -n -s /root/sd_webui/cache/huggingface/huggingface_repo/* /root/sd_webui/sd_main_dir/log
[ -0.7627964615821838, -0.19222764670848846, 0.12659841775894165, 0.6476641893386841, -0.5734990835189819, 0.4627455472946167, 0.18533553183078766, 0.003375691594555974, 0.9853092432022095, 0.5556601881980896, -1.1237943172454834, -0.39997735619544983, -0.7013154029846191, 0.5654587745666504...
null
null
null
null
null
null
null
null
null
null
null
null
null
IliyanGochev/common_voice_13_0_bg_pseudo_labelled
IliyanGochev
2023-11-28T10:27:00Z
0
0
null
[ "region:us" ]
2023-11-28T10:27:00Z
2023-11-28T09:42:38.000Z
2023-11-28T09:42:38
--- dataset_info: config_name: bg features: - name: client_id dtype: string - name: path dtype: string - name: audio dtype: audio: sampling_rate: 16000 - name: sentence dtype: string - name: up_votes dtype: int64 - name: down_votes dtype: int64 - name: age dtype: string - name: gender dtype: string - name: accent dtype: string - name: locale dtype: string - name: segment dtype: string - name: variant dtype: string - name: whisper_transcript sequence: int64 splits: - name: train num_bytes: 92489982.56 num_examples: 3385 - name: validation num_bytes: 79482559.912 num_examples: 2358 - name: test num_bytes: 84919243.036 num_examples: 2463 download_size: 265321822 dataset_size: 256891785.50800002 configs: - config_name: bg data_files: - split: train path: bg/train-* - split: validation path: bg/validation-* - split: test path: bg/test-* ---
[ -0.1285335123538971, -0.1861683875322342, 0.6529128551483154, 0.49436232447624207, -0.19319400191307068, 0.23607441782951355, 0.36072009801864624, 0.05056373029947281, 0.5793656706809998, 0.7400146722793579, -0.650810182094574, -0.23784008622169495, -0.7102247476577759, -0.0478255338966846...
null
null
null
null
null
null
null
null
null
null
null
null
null
satpalsr/filter
satpalsr
2023-11-28T09:52:31Z
0
0
null
[ "region:us" ]
2023-11-28T09:52:31Z
2023-11-28T09:51:04.000Z
2023-11-28T09:51:04
Entry not found
[ -0.32276472449302673, -0.22568407654762268, 0.8622258901596069, 0.4346148371696472, -0.5282984972000122, 0.7012965679168701, 0.7915717363357544, 0.07618629932403564, 0.7746022939682007, 0.2563222646713257, -0.785281777381897, -0.22573848068714142, -0.9104482531547546, 0.5715669393539429, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
Andron00e/CIFAR100-custom
Andron00e
2023-11-28T10:00:58Z
0
0
null
[ "task_categories:image-classification", "size_categories:10K<n<100K", "language:en", "license:mit", "region:us" ]
2023-11-28T10:00:58Z
2023-11-28T09:51:12.000Z
2023-11-28T09:51:12
--- dataset_info: features: - name: image_file_path dtype: string - name: image dtype: image - name: labels dtype: int64 splits: - name: train num_bytes: 59505360 num_examples: 60000 download_size: 27123594 dataset_size: 59505360 configs: - config_name: default data_files: - split: train path: data/train-* license: mit task_categories: - image-classification language: - en size_categories: - 10K<n<100K --- Example of usage: ```python from datasets import load_dataset dataset = load_dataset("Andron00e/CIFAR100-custom") splitted_dataset = dataset["train"].train_test_split(test_size=0.2) ```
[ -0.5434361696243286, -0.3428143858909607, -0.18200275301933289, 0.15259936451911926, -0.19185258448123932, -0.18169787526130676, 0.0791841596364975, 0.11102788895368576, 0.09916254132986069, 0.3320888578891754, -0.33155521750450134, 0.06812416017055511, -0.12859667837619781, 0.242264166474...
null
null
null
null
null
null
null
null
null
null
null
null
null
satpalsr/question
satpalsr
2023-11-28T09:53:22Z
0
0
null
[ "region:us" ]
2023-11-28T09:53:22Z
2023-11-28T09:51:36.000Z
2023-11-28T09:51:36
Entry not found
[ -0.32276472449302673, -0.22568407654762268, 0.8622258901596069, 0.4346148371696472, -0.5282984972000122, 0.7012965679168701, 0.7915717363357544, 0.07618629932403564, 0.7746022939682007, 0.2563222646713257, -0.785281777381897, -0.22573848068714142, -0.9104482531547546, 0.5715669393539429, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
Rami/sketch_to_hed
Rami
2023-11-28T09:51:46Z
0
0
null
[ "region:us" ]
2023-11-28T09:51:46Z
2023-11-28T09:51:40.000Z
2023-11-28T09:51:40
--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': test '1': train '2': validation splits: - name: train num_bytes: 400653.0 num_examples: 10 - name: validation num_bytes: 363040.0 num_examples: 12 - name: test num_bytes: 1224181.0 num_examples: 40 download_size: 1727421 dataset_size: 1987874.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
Rami/sketch_to_next_sketch
Rami
2023-11-28T09:52:49Z
0
0
null
[ "region:us" ]
2023-11-28T09:52:49Z
2023-11-28T09:52:01.000Z
2023-11-28T09:52:01
--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': test '1': train '2': validation splits: - name: train num_bytes: 12459154.07 num_examples: 1278 - name: validation num_bytes: 11271129.782 num_examples: 1071 - name: test num_bytes: 30001683.886 num_examples: 2978 download_size: 51938025 dataset_size: 53731967.738 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---
[ -0.1285335123538971, -0.1861683875322342, 0.6529128551483154, 0.49436232447624207, -0.19319400191307068, 0.23607441782951355, 0.36072009801864624, 0.05056373029947281, 0.5793656706809998, 0.7400146722793579, -0.650810182094574, -0.23784008622169495, -0.7102247476577759, -0.0478255338966846...
null
null
null
null
null
null
null
null
null
null
null
null
null
ksmemory/FTA
ksmemory
2023-11-28T10:16:17Z
0
0
null
[ "region:us" ]
2023-11-28T10:16:17Z
2023-11-28T09:54:29.000Z
2023-11-28T09:54:29
Entry not found
[ -0.3227645754814148, -0.22568479180335999, 0.8622264862060547, 0.43461528420448303, -0.52829909324646, 0.7012971639633179, 0.7915720343589783, 0.07618614286184311, 0.774603009223938, 0.2563217282295227, -0.7852813005447388, -0.22573819756507874, -0.9104477167129517, 0.5715674161911011, -...
null
null
null
null
null
null
null
null
null
null
null
null
null
Sefaria/english_library
Sefaria
2023-11-28T10:21:12Z
0
0
null
[ "license:gpl-3.0", "region:us" ]
2023-11-28T10:21:12Z
2023-11-28T09:58:25.000Z
2023-11-28T09:58:25
--- license: gpl-3.0 --- # Description Export of Sefaria's English library data. This data represents over version in the library marked as English. ## Schema | Field | Description | | --- | --- | | text | The text of a single segment in the library. A segment is the smallest chunk of test, usually representing a paragraph. | | metadata | Dictionary of metadata. See below for schema. | ### Metadata Schema | Field | Description | | --- | --- | | url | URL to this segment in Sefaria | | ref | Canonical Ref to this segment. Refs are a human readable ID that is unique independent of version. Different versions of a segment all share the same Ref. | | versionTitle | Version title of the version this segment came from. | | lang | two letter language code. | | docCategory | Category for this segment. This corresponds to where the segment's book is located in Sefaria's table of contents. | | dataQuality | Estimate of the quality of the text. This can be either "professional" or "user". | | pagerank | Pagerank for this segment calculated using Sefaria's internal link graph. Higher values indicate the segment is more centrally cited by sources. |
[ -0.5709785223007202, -0.4688186049461365, 0.12514632940292358, 0.09684384614229202, -0.5182107090950012, 0.06000272557139397, 0.3785896599292755, -0.46849116683006287, 0.6707982420921326, 0.6797115802764893, -0.7310574650764465, -0.7523360848426819, -0.1941734403371811, 0.24721075594425201...
null
null
null
null
null
null
null
null
null
null
null
null
null
Kuro0911/phishing_url_llama
Kuro0911
2023-11-28T09:59:28Z
0
0
null
[ "license:mit", "region:us" ]
2023-11-28T09:59:28Z
2023-11-28T09:59:24.000Z
2023-11-28T09:59:24
--- license: mit ---
[ -0.1285335123538971, -0.1861683875322342, 0.6529128551483154, 0.49436232447624207, -0.19319400191307068, 0.23607441782951355, 0.36072009801864624, 0.05056373029947281, 0.5793656706809998, 0.7400146722793579, -0.650810182094574, -0.23784008622169495, -0.7102247476577759, -0.0478255338966846...
null
null
null
null
null
null
null
null
null
null
null
null
null
nateraw/english-to-hinglish
nateraw
2023-11-28T21:16:58Z
0
0
null
[ "region:us" ]
2023-11-28T21:16:58Z
2023-11-28T10:01:50.000Z
2023-11-28T10:01:50
--- dataset_info: features: - name: en dtype: string - name: hi_ng dtype: string - name: source dtype: int64 splits: - name: train num_bytes: 18814411 num_examples: 178701 - name: test num_bytes: 1098000 num_examples: 10401 download_size: 11924718 dataset_size: 19912411 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* --- Fork of [findnitai/english-to-hinglish](https://huggingface.co/datasets/findnitai/english-to-hinglish) that splits the training set into train/test.
[ -0.6194483637809753, -0.6102665066719055, -0.18711170554161072, 0.41961196064949036, -0.12454678118228912, 0.03989695757627487, -0.025993788614869118, -0.56533282995224, 1.0325169563293457, 0.6787667870521545, -0.9221007227897644, -0.10635977238416672, -0.512734591960907, 0.051245339214801...
null
null
null
null
null
null
null
null
null
null
null
null
null
reza-alipour/CelebA-HQ-Seg
reza-alipour
2023-11-28T10:56:43Z
0
0
null
[ "region:us" ]
2023-11-28T10:56:43Z
2023-11-28T10:18:16.000Z
2023-11-28T10:18:16
--- dataset_info: features: - name: id dtype: string - name: mm_id dtype: string - name: image dtype: image - name: mask dtype: image - name: landmark dtype: image - name: landmark_cropped dtype: image - name: captions sequence: string - name: captions_eng sequence: string - name: captions_pes sequence: string - name: captions_cmn sequence: string - name: captions_fra sequence: string - name: captions_deu sequence: string - name: captions_ita sequence: string - name: captions_spa sequence: string - name: captions_all sequence: string - name: mask_segformer dtype: image splits: - name: train num_bytes: 3885530945.625 num_examples: 28495 - name: test num_bytes: 231063342.75 num_examples: 1498 download_size: 3829867987 dataset_size: 4116594288.375 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
[ -0.1285335123538971, -0.1861683875322342, 0.6529128551483154, 0.49436232447624207, -0.19319400191307068, 0.23607441782951355, 0.36072009801864624, 0.05056373029947281, 0.5793656706809998, 0.7400146722793579, -0.650810182094574, -0.23784008622169495, -0.7102247476577759, -0.0478255338966846...
null
null
null
null
null
null
null
null
null
null
null
null
null
Sefaria/hebrew_library
Sefaria
2023-11-28T10:47:51Z
0
0
null
[ "license:gpl-3.0", "region:us" ]
2023-11-28T10:47:51Z
2023-11-28T10:23:03.000Z
2023-11-28T10:23:03
--- license: gpl-3.0 --- # Description Export of Sefaria's Hebrew library data. This data represents over version in the library marked as Hebrew. ## Schema | Field | Description | | --- | --- | | text | The text of a single segment in the library. A segment is the smallest chunk of test, usually representing a paragraph. | | metadata | Dictionary of metadata. See below for schema. | ### Metadata Schema | Field | Description | | --- | --- | | url | URL to this segment in Sefaria | | ref | Canonical Ref to this segment. Refs are a human readable ID that is unique independent of version. Different versions of a segment all share the same Ref. | | versionTitle | Version title of the version this segment came from. | | lang | two letter language code. | | docCategory | Category for this segment. This corresponds to where the segment's book is located in Sefaria's table of contents. | | dataQuality | Estimate of the quality of the text. This can be either "professional" or "user". | | pagerank | Pagerank for this segment calculated using Sefaria's internal link graph. Higher values indicate the segment is more centrally cited by sources. |
[ -0.5023195743560791, -0.5028815269470215, 0.01463149394840002, 0.09836933016777039, -0.5430060625076294, -0.001991128781810403, 0.35290706157684326, -0.4012186527252197, 0.6028505563735962, 0.6482463479042053, -0.7034521102905273, -0.9032110571861267, -0.25857630372047424, 0.06152109056711...
null
null
null
null
null
null
null
null
null
null
null
null
null
amaye15/Stack-Overflow-Zero-Shot-Classification
amaye15
2023-11-28T10:38:54Z
0
0
null
[ "region:us" ]
2023-11-28T10:38:54Z
2023-11-28T10:29:35.000Z
2023-11-28T10:29:35
--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: Date dtype: string - name: Title dtype: string - name: Tags dtype: string - name: Score dtype: int64 splits: - name: train num_bytes: 66744845 num_examples: 553439 download_size: 25302295 dataset_size: 66744845 --- # Dataset Card for "Stack-Overflow-Zero-Shot-Classification" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.43892788887023926, -0.36368483304977417, 0.18197393417358398, -0.09502231329679489, -0.031671009957790375, 0.24588212370872498, 0.44675904512405396, -0.2251293808221817, 0.5963051915168762, 0.5119502544403076, -0.5820396542549133, -0.9227556586265564, -0.6419802904129028, -0.53062248229...
null
null
null
null
null
null
null
null
null
null
null
null
null
nateraw/replicate-training-datasets
nateraw
2023-11-28T10:31:24Z
0
0
null
[ "region:us" ]
2023-11-28T10:31:24Z
2023-11-28T10:30:52.000Z
2023-11-28T10:30:52
Entry not found
[ -0.32276472449302673, -0.22568407654762268, 0.8622258901596069, 0.4346148371696472, -0.5282984972000122, 0.7012965679168701, 0.7915717363357544, 0.07618629932403564, 0.7746022939682007, 0.2563222646713257, -0.785281777381897, -0.22573848068714142, -0.9104482531547546, 0.5715669393539429, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
Shubbair/oxford_flowers
Shubbair
2023-11-28T13:33:29Z
0
0
null
[ "region:us" ]
2023-11-28T13:33:29Z
2023-11-28T10:31:04.000Z
2023-11-28T10:31:04
--- dataset_info: features: - name: image dtype: image splits: - name: train num_bytes: 3015452.0 num_examples: 102 download_size: 3016707 dataset_size: 3015452.0 configs: - config_name: default data_files: - split: train path: data/train-* ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
NobodyExistsOnTheInternet/turbotoconvert
NobodyExistsOnTheInternet
2023-11-28T10:38:02Z
0
0
null
[ "license:mit", "region:us" ]
2023-11-28T10:38:02Z
2023-11-28T10:35:49.000Z
2023-11-28T10:35:49
--- license: mit ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
roupenminassian/vehicle-dataset-v4
roupenminassian
2023-11-28T10:46:14Z
0
0
null
[ "region:us" ]
2023-11-28T10:46:14Z
2023-11-28T10:44:35.000Z
2023-11-28T10:44:35
--- 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: int64 splits: - name: train num_bytes: 151700808.768 num_examples: 1364 download_size: 149189451 dataset_size: 151700808.768 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "vehicle-dataset-v4" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.6726629137992859, 0.08265996724367142, 0.43860694766044617, 0.2288210093975067, -0.2468220293521881, 0.04945574700832367, 0.5175250172615051, -0.273931086063385, 0.525201141834259, 0.372847318649292, -1.0186015367507935, -0.6318637728691101, -0.3005826771259308, -0.30637115240097046, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
imone/FLAN_NIv2_NoExplanation
imone
2023-11-28T10:56:20Z
0
0
null
[ "license:mit", "region:us" ]
2023-11-28T10:56:20Z
2023-11-28T10:48:30.000Z
2023-11-28T10:48:30
--- license: mit --- # FLAN NIv2 without explanation This is a subset of [FLAN NIv2](https://huggingface.co/datasets/Open-Orca/FLAN). We removed all examples with explanations in the few-shot template, as the final answers also don't have explanations.
[ -0.40104830265045166, -0.7325344085693359, 0.20814265310764313, -0.014485925436019897, -0.43644848465919495, -0.27320507168769836, 0.3724297285079956, -0.2556949555873871, 0.5550204515457153, 0.5986126065254211, -1.2683199644088745, -0.22574763000011444, -0.33921146392822266, -0.0789861902...
null
null
null
null
null
null
null
null
null
null
null
null
null
Sefaria/links
Sefaria
2023-11-28T11:04:51Z
0
0
null
[ "license:gpl-3.0", "region:us" ]
2023-11-28T11:04:51Z
2023-11-28T10:52:14.000Z
2023-11-28T10:52:14
--- license: gpl-3.0 ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
Linaqruf/frieren-xl-lora-test
Linaqruf
2023-11-28T11:04:01Z
0
0
null
[ "region:us" ]
2023-11-28T11:04:01Z
2023-11-28T10:57:47.000Z
2023-11-28T10:57:47
Entry not found
[ -0.32276472449302673, -0.22568407654762268, 0.8622258901596069, 0.4346148371696472, -0.5282984972000122, 0.7012965679168701, 0.7915717363357544, 0.07618629932403564, 0.7746022939682007, 0.2563222646713257, -0.785281777381897, -0.22573848068714142, -0.9104482531547546, 0.5715669393539429, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
James332/tt3
James332
2023-11-28T11:31:31Z
0
0
null
[ "region:us" ]
2023-11-28T11:31:31Z
2023-11-28T11:02:14.000Z
2023-11-28T11:02:14
--- dataset_info: features: - name: image dtype: image - name: question_type dtype: string - name: confidence dtype: int32 - name: answers sequence: string - name: answers_original list: - name: answer dtype: string - name: raw_answer dtype: string - name: answer_confidence dtype: string - name: answer_id dtype: int64 - name: id_image dtype: int64 - name: answer_type dtype: string - name: question_id dtype: int64 - name: question dtype: string - name: id dtype: int64 - name: clip_tags_ViT_L_14 sequence: string - name: clip_tags_LAION_ViT_H_14_2B sequence: string - name: blip_caption_beam_5 dtype: string - name: LLM_Description_gpt3_downstream_tasks_visual_genome_ViT_L_14 sequence: string - name: LLM_Description_gpt3_downstream_tasks_visual_genome_LAION-ViT-H-14-2B sequence: string - name: DETA_detections_deta_swin_large_o365_coco_classes list: - name: attribute dtype: string - name: box sequence: float32 - name: label dtype: string - name: location dtype: string - name: ratio dtype: float32 - name: size dtype: string - name: tag dtype: string - name: DETA_detections_deta_swin_large_o365_coco_classes_caption_module_random list: - name: attribute dtype: string - name: box sequence: float64 - name: captions_module sequence: string - name: captions_module_filter sequence: string - name: label dtype: string - name: location dtype: string - name: ratio dtype: float64 - name: size dtype: string - name: tag dtype: string splits: - name: train num_bytes: 1686555802.0 num_examples: 9009 download_size: 1572400067 dataset_size: 1686555802.0 --- # Dataset Card for "OK-VQA_train" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.719218373298645, -0.1172432228922844, 0.29995885491371155, -0.07760744541883469, -0.13567519187927246, -0.2137058675289154, 0.4510095715522766, -0.07949715107679367, 0.6381325125694275, 0.49382418394088745, -0.838329553604126, -0.46737974882125854, -0.47145941853523254, -0.4232290983200...
null
null
null
null
null
null
null
null
null
null
null
null
null
Shawt/liz
Shawt
2023-11-28T11:26:54Z
0
0
null
[ "license:openrail", "art", "lizz", "region:us" ]
2023-11-28T11:26:54Z
2023-11-28T11:12:58.000Z
2023-11-28T11:12:58
--- license: openrail tags: - art - lizz --- # 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 <!-- Provide a longer summary of what this dataset is. --> - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- 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. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
[ -0.5322356224060059, -0.5534716844558716, 0.1290130317211151, 0.23470577597618103, -0.39626216888427734, -0.11762470006942749, -0.03545305132865906, -0.6389272212982178, 0.5699822306632996, 0.7838326692581177, -0.7834625840187073, -0.9173274040222168, -0.55633145570755, 0.13078093528747559...
null
null
null
null
null
null
null
null
null
null
null
null
null
bashmanxx/llama37train
bashmanxx
2023-11-28T11:16:10Z
0
0
null
[ "region:us" ]
2023-11-28T11:16:10Z
2023-11-28T11:16:00.000Z
2023-11-28T11:16:00
--- dataset_info: features: - name: text struct: - name: text struct: - name: text dtype: string splits: - name: train num_bytes: 495601 num_examples: 420 download_size: 44997 dataset_size: 495601 configs: - config_name: default data_files: - split: train path: data/train-* ---
[ -0.1285335123538971, -0.1861683875322342, 0.6529128551483154, 0.49436232447624207, -0.19319400191307068, 0.23607441782951355, 0.36072009801864624, 0.05056373029947281, 0.5793656706809998, 0.7400146722793579, -0.650810182094574, -0.23784008622169495, -0.7102247476577759, -0.0478255338966846...
null
null
null
null
null
null
null
null
null
null
null
null
null
Shubbair/oxford_flowers_102
Shubbair
2023-11-28T11:19:39Z
0
0
null
[ "region:us" ]
2023-11-28T11:19:39Z
2023-11-28T11:19:26.000Z
2023-11-28T11:19:26
--- dataset_info: features: - name: image dtype: image splits: - name: train num_bytes: 3015452.0 num_examples: 102 download_size: 3016707 dataset_size: 3015452.0 configs: - config_name: default data_files: - split: train path: data/train-* ---
[ -0.1285335123538971, -0.1861683875322342, 0.6529128551483154, 0.49436232447624207, -0.19319400191307068, 0.23607441782951355, 0.36072009801864624, 0.05056373029947281, 0.5793656706809998, 0.7400146722793579, -0.650810182094574, -0.23784008622169495, -0.7102247476577759, -0.0478255338966846...
null
null
null
null
null
null
null
null
null
null
null
null
null
erbacher/testdata
erbacher
2023-11-28T11:25:56Z
0
0
null
[ "region:us" ]
2023-11-28T11:25:56Z
2023-11-28T11:25:25.000Z
2023-11-28T11:25:25
--- dataset_info: features: - name: parameters dtype: string - name: tensor sequence: sequence: sequence: float32 - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 22205500 num_examples: 100 download_size: 2695407 dataset_size: 22205500 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "testdata" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.590869665145874, -0.30755072832107544, 0.19610433280467987, 0.09336929768323898, -0.07715299725532532, 0.1159442588686943, 0.23835550248622894, -0.08274070918560028, 0.7648308873176575, 0.32310783863067627, -0.7559483647346497, -0.7884511947631836, -0.47454148530960083, -0.2563454508781...
null
null
null
null
null
null
null
null
null
null
null
null
null
alvarobartt/HelpSteer-AIF
alvarobartt
2023-11-28T15:09:56Z
0
0
null
[ "size_categories:n<1K", "language:en", "license:cc-by-4.0", "distilabel", "helpsteer", "gpt-4", "aif", "arxiv:2311.09528", "region:us" ]
2023-11-28T15:09:56Z
2023-11-28T11:41:53.000Z
2023-11-28T11:41:53
--- language: - en license: cc-by-4.0 size_categories: - n<1K pretty_name: HelpSteer with AIF dataset_info: features: - name: prompt dtype: string - name: response dtype: string - name: model dtype: string - name: correctness dtype: int64 - name: coherence dtype: int64 - name: complexity dtype: int64 - name: verbosity dtype: int64 - name: helpfulness dtype: int64 splits: - name: train num_bytes: 2832095 num_examples: 1000 download_size: 677100 dataset_size: 2832095 configs: - config_name: default data_files: - split: train path: data/train-* tags: - distilabel - helpsteer - gpt-4 - aif --- # HelpSteer: Helpfulness SteerLM Dataset HelpSteer is an open-source Helpfulness Dataset (CC-BY-4.0) that supports aligning models to become more helpful, factually correct and coherent, while being adjustable in terms of the complexity and verbosity of its responses. [HelpSteer: Multi-attribute Helpfulness Dataset for SteerLM](http://arxiv.org/abs/2311.09528) ## Disclaimer This is only a subset created with `distilabel` to evaluate the first 100 rows using AI Feedback (AIF) coming from GPT-4, only created for experimenting / research purposes, please refer to [nvidia/HelpSteer](https://hf.co/nvidia/HelpSteer) if you want more information about the HelpSteer dataset. ## Dataset Description HelpSteer contains 37120 samples, while this subset only contains the first 100, each containing a prompt, a response as well as five human-annotated attributes of the response, each ranging between 0 and 4 where higher means better for each attribute. These attributes are: 1. **Helpfulness**: Overall helpfulness of the response to the prompt. 2. **Correctness**: Inclusion of all pertinent facts without errors. 3. **Coherence**: Consistency and clarity of expression. 4. **Complexity**: Intellectual depth required to write response (i.e. whether the response can be written by anyone with basic language competency or requires deep domain expertise). 5. **Verbosity**: Amount of detail included in the response, relative to what is asked for in the prompt. ## Source 1. Prompts are collected based on a mixture of template-generated (mainly for prompt involving long reference text) and human generated by Scale AI. These prompts relate to the tasks of Rewrite, Summarization, Classification, Extraction, Closed Question Answering, Open Question Answering, Generation and Brainstorming. 2. Responses are generated by an early version of an inhouse LLM. We generate up to 4 responses per prompts using sample techniques to give diverse yet reasonable responses. 3. Annotations of various attributes were done by Scale AI. Annotators rated each response on a Likert 5 scale (between 0 and 4) for each attribute (helpfulness, correctness, coherence, complexity and verbosity). ## Annotation methodology (short) 1. We engaged a select group of contractors via Scale AI. These contractors were provided with comprehensive guidelines that defined each attribute and the criteria for every rating level, together with some annotated examples. These guidelines and examples are detailed in the Appendix of the accompanying paper. 2. The annotation process involved approximately 200 U.S.-based human annotators. Candidates first underwent preliminary assignments, including assessments of English proficiency, to determine eligibility for working on the project. Subsequently, they participated in an introductory training course on the task which ended with a test that involved annotating 35 sample responses. This process ensured not only a thorough understanding of the task requirements but also the delivery of high-quality annotations. 3. Post-annotations, Scale AI performed extensive quality assurance, with each annotation reaching a minimum of two human reviews in addition to automated checks. After receiving the annotations from Scale AI, we conducted our independent quality assurance to make sure that the quality of the annotations was up to our expectations. As a result, some annotations were filtered away to retain only 37, 120 samples. ## Citation If you find this dataset useful, please cite the work from the original authors. ```bibtex @misc{wang2023helpsteer, title={HelpSteer: Multi-attribute Helpfulness Dataset for SteerLM}, author={Zhilin Wang and Yi Dong and Jiaqi Zeng and Virginia Adams and Makesh Narsimhan Sreedhar and Daniel Egert and Olivier Delalleau and Jane Polak Scowcroft and Neel Kant and Aidan Swope and Oleksii Kuchaiev}, year={2023}, eprint={2311.09528}, archivePrefix={arXiv}, primaryClass={cs.CL} } ```
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Gbssreejith/death
Gbssreejith
2023-11-28T11:55:55Z
0
0
null
[ "region:us" ]
2023-11-28T11:55:55Z
2023-11-28T11:51:01.000Z
2023-11-28T11:51:01
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: val path: data/val-* dataset_info: features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 26946635.0 num_examples: 51 - name: test num_bytes: 3183225.0 num_examples: 6 - name: val num_bytes: 3661207.0 num_examples: 7 download_size: 33726877 dataset_size: 33791067.0 --- # Dataset Card for "death" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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null
null
null
null
null
null
null
null
null
null
null
null
null
indiejoseph/commoncrawl_cantonese
indiejoseph
2023-11-28T11:57:17Z
0
0
null
[ "license:mit", "region:us" ]
2023-11-28T11:57:17Z
2023-11-28T11:57:15.000Z
2023-11-28T11:57:15
--- license: mit ---
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null
null
null
null
null
null
null
null
null
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null
null
tim9292654/setting-config
tim9292654
2023-11-28T15:30:35Z
0
0
null
[ "region:us" ]
2023-11-28T15:30:35Z
2023-11-28T12:01:28.000Z
2023-11-28T12:01:28
Entry not found
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null
null
null
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null
isek-ai/danbooru-tags-2016-2023
isek-ai
2023-11-28T13:03:24Z
0
0
null
[ "task_categories:text-classification", "task_categories:text-generation", "task_categories:text2text-generation", "size_categories:1M<n<10M", "language:en", "license:cc0-1.0", "danbooru", "region:us" ]
2023-11-28T13:03:24Z
2023-11-28T12:11:20.000Z
2023-11-28T12:11:20
--- dataset_info: - config_name: all features: - name: id dtype: int64 - name: copyright dtype: string - name: character dtype: string - name: artist dtype: string - name: general dtype: string - name: meta dtype: string - name: rating dtype: string - name: score dtype: int64 - name: created_at dtype: string splits: - name: train num_bytes: 2443978290 num_examples: 4488788 download_size: 966023700 dataset_size: 2443978290 - config_name: safe features: - name: id dtype: int64 - name: copyright dtype: string - name: character dtype: string - name: artist dtype: string - name: general dtype: string - name: meta dtype: string - name: rating dtype: string - name: score dtype: int64 - name: created_at dtype: string splits: - name: train num_bytes: 616013975.4781559 num_examples: 1131416 download_size: 235094331 dataset_size: 616013975.4781559 configs: - config_name: all data_files: - split: train path: all/train-* - config_name: safe data_files: - split: train path: safe/train-* license: cc0-1.0 task_categories: - text-classification - text-generation - text2text-generation language: - en tags: - danbooru size_categories: - 1M<n<10M --- # danbooru-tags-2016-2023 A dataset of danbooru tags. ## Dataset information Generated using [danbooru](https://danbooru.donmai.us/) and [safebooru](https://safebooru.donmai.us/) API. The dataset was created with the following conditions: |Subset name|`all`|`safe`| |-|-|-| |API Endpoint|https://danbooru.donmai.us|https://safebooru.donmai.us| |Date|`2016-01-01..2023-11-27`|`2016-01-01..2023-11-26`| |Score|`>0`|`>0`| |Rating|`g,s,q,e`|`g`| |Filetype|`png,jpg,webp`|`png,jpg,webp`| |Size (number of rows)|4,488,788|1,131,416| ## Usage ``` pip install datasets ``` ```py from datasets import load_dataset dataset = load_dataset( "isek-ai/danbooru-tags-2016-2023", "safe", # or "all" split="train", ) print(dataset) print(dataset[0]) # Dataset({ # features: ['id', 'copyright', 'character', 'artist', 'general', 'meta', 'rating', 'score', 'created_at'], # num_rows: 1131416 # }) # {'id': 2229839, 'copyright': 'kara no kyoukai', 'character': 'ryougi shiki', 'artist': 'momoko (momopoco)', 'general': '1girl, 2016, :|, brown eyes, brown hair, closed mouth, cloud, cloudy sky, dated, day, flower, hair flower, hair ornament, japanese clothes, kimono, long hair, long sleeves, looking at viewer, new year, obi, outdoors, sash, shrine, sky, solo, standing, wide sleeves', 'meta': 'commentary request, partial commentary', 'rating': 'g', 'score': 76, 'created_at': '2016-01-01T00:43:18.369+09:00'} ```
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joseluhf11/oct-fovea-detection
joseluhf11
2023-11-28T12:15:09Z
0
0
null
[ "region:us" ]
2023-11-28T12:15:09Z
2023-11-28T12:14:41.000Z
2023-11-28T12:14:41
--- dataset_info: features: - name: image dtype: image - name: objects struct: - name: bbox sequence: sequence: int64 - name: categories sequence: string splits: - name: train num_bytes: 350015166.0 num_examples: 431 download_size: 349205446 dataset_size: 350015166.0 configs: - config_name: default data_files: - split: train path: data/train-* ---
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null
null
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null
null
null
BangorAI/exl2-wiki-calibration-set-cy
BangorAI
2023-11-28T16:41:25Z
0
0
null
[ "license:cc-by-sa-3.0", "region:us" ]
2023-11-28T16:41:25Z
2023-11-28T12:14:53.000Z
2023-11-28T12:14:53
--- license: cc-by-sa-3.0 --- ### Data Calibro Exl2 Detholiad o [Cofnod y Cynulliad](https://huggingface.co/datasets/techiaith/cofnodycynulliad_en-cy) Cymraeg i'w ddefnyddio yng ngham calibro ExLlama 2 wrth drosi modelau i fformat exl2.
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null
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null
null
null
ddps007/test-dataset-v8
ddps007
2023-11-28T12:17:51Z
0
0
null
[ "region:us" ]
2023-11-28T12:17:51Z
2023-11-28T12:17:49.000Z
2023-11-28T12:17:49
Entry not found
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null
null
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null
null
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null
null
null
null
ddps007/test-dataset-v10
ddps007
2023-11-28T12:18:15Z
0
0
null
[ "region:us" ]
2023-11-28T12:18:15Z
2023-11-28T12:18:14.000Z
2023-11-28T12:18:14
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
Alexandre-Numind/BenchFew
Alexandre-Numind
2023-11-28T12:20:02Z
0
0
null
[ "region:us" ]
2023-11-28T12:20:02Z
2023-11-28T12:19:26.000Z
2023-11-28T12:19:26
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
ddps007/test-dd
ddps007
2023-11-29T00:43:14Z
0
0
null
[ "region:us" ]
2023-11-29T00:43:14Z
2023-11-28T12:19:44.000Z
2023-11-28T12:19:44
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
Alexandre-Numind/BenchNoFew
Alexandre-Numind
2023-11-28T12:22:37Z
0
0
null
[ "region:us" ]
2023-11-28T12:22:37Z
2023-11-28T12:21:59.000Z
2023-11-28T12:21:59
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
Alexandre-Numind/IE_FS
Alexandre-Numind
2023-11-28T12:24:10Z
0
0
null
[ "region:us" ]
2023-11-28T12:24:10Z
2023-11-28T12:23:29.000Z
2023-11-28T12:23:29
Entry not found
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null
null
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null
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null
null
null
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null
null
null
null
SanaFalakJ/IA
SanaFalakJ
2023-11-28T12:29:15Z
0
0
null
[ "region:us" ]
2023-11-28T12:29:15Z
2023-11-28T12:29:10.000Z
2023-11-28T12:29:10
--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 64521 num_examples: 19 download_size: 41947 dataset_size: 64521 configs: - config_name: default data_files: - split: train path: data/train-* ---
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null
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null
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null
null
null
null
null
null
null
null
fabsss/westfalmelado
fabsss
2023-11-28T12:30:03Z
0
0
null
[ "license:apache-2.0", "region:us" ]
2023-11-28T12:30:03Z
2023-11-28T12:29:18.000Z
2023-11-28T12:29:18
--- license: apache-2.0 ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
yimhuang/guanaco-llama2-1k
yimhuang
2023-11-28T12:38:21Z
0
0
null
[ "region:us" ]
2023-11-28T12:38:21Z
2023-11-28T12:30:09.000Z
2023-11-28T12:30:09
--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 1654448 num_examples: 1000 download_size: 966693 dataset_size: 1654448 configs: - config_name: default data_files: - split: train path: data/train-* --- # Guanaco-1k: Lazy Llama 2 Formatting This is a subset (1000 samples) of the excellent [`timdettmers/openassistant-guanaco`](https://huggingface.co/datasets/timdettmers/openassistant-guanaco) dataset, processed to match Llama 2's prompt format as described [in this article](https://huggingface.co/blog/llama2#how-to-prompt-llama-2). It was created using the following [colab notebook](https://colab.research.google.com/drive/1Ad7a9zMmkxuXTOh1Z7-rNSICA4dybpM2?usp=sharing). Useful if you don't want to reformat it by yourself (e.g., using a script). It was designed for [this article](https://mlabonne.github.io/blog/posts/Fine_Tune_Your_Own_Llama_2_Model_in_a_Colab_Notebook.html) about fine-tuning a Llama 2 (chat) model in a Google Colab.
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null
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null
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zinc75/Vibravox_dummy
zinc75
2023-11-28T20:36:39Z
0
0
null
[ "task_categories:audio-to-audio", "task_categories:automatic-speech-recognition", "task_categories:audio-classification", "task_categories:text-to-speech", "task_ids:speaker-identification", "annotations_creators:expert-generated", "language_creators:crowdsourced", "language_creators:expert-generated"...
2023-11-28T20:36:39Z
2023-11-28T12:33:43.000Z
2023-11-28T12:33:43
--- license: cc-by-4.0 task_categories: - audio-to-audio - automatic-speech-recognition - audio-classification - text-to-speech task_ids: - speaker-identification size_categories: - 10K<n<100K source_datasets: [] language: - fr multilinguality: - monolingual language_creators: - crowdsourced - expert-generated annotations_creators: - expert-generated pretty_name: 'VibraVox' configs: - config_name: ASR_Reference_microphone data_files: - split: train path: "train_ASR_ref_microphone.tsv" - split: val path: "val_ASR_ref_microphone.tsv" - split: test path: "test_ASR_ref_microphone.tsv" - config_name: ASR_Laryngophone features: - name: file_name dtype: string - name: audio dtype: audio - name: transcription dtype: string - name: sensor_id dtype: string - name: speaker_id dtype: int64 - name: gender dtype: string - name: type dtype: string - name: gender dtype: string - name: split dtype: string data_files: - split: train path: "train_ASR_laryngophone.tsv" - split: val path: "val_ASR_laryngophone.tsv" - split: test path: "test_ASR_laryngophone.tsv" ---
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null
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vishnu027/death
vishnu027
2023-11-28T12:48:17Z
0
0
null
[ "region:us" ]
2023-11-28T12:48:17Z
2023-11-28T12:34:05.000Z
2023-11-28T12:34:05
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: val path: data/val-* dataset_info: features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 749731844.0 num_examples: 560 - name: test num_bytes: 97083916.0 num_examples: 70 - name: val num_bytes: 95493624.0 num_examples: 70 download_size: 940687614 dataset_size: 942309384.0 --- # Dataset Card for "death" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.4540598392486572, -0.2858071029186249, 0.4648527204990387, 0.26601991057395935, -0.40429848432540894, 0.13919086754322052, 0.33589306473731995, -0.10595114529132843, 0.9028188586235046, 0.5282403230667114, -0.8842339515686035, -0.8634734153747559, -0.5942906141281128, -0.428038775920867...
null
null
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null
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null
null
TeeA/Vietnamese-Chart-Dataset
TeeA
2023-11-28T13:41:25Z
0
0
null
[ "region:us" ]
2023-11-28T13:41:25Z
2023-11-28T12:35:29.000Z
2023-11-28T12:35:29
--- dataset_info: features: - name: title dtype: string - name: x_title dtype: string - name: y_title dtype: string - name: x dtype: string - name: y dtype: string - name: file_name dtype: string - name: chart_type dtype: string - name: image dtype: image splits: - name: train num_bytes: 115631536.42857143 num_examples: 5000 - name: test num_bytes: 23422771.285714287 num_examples: 1000 - name: validation num_bytes: 23502759.285714287 num_examples: 1000 download_size: 116048333 dataset_size: 162557067.00000003 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: validation path: data/validation-* ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
ctoraman/BilTweetNews-Sentiment
ctoraman
2023-11-28T12:41:24Z
0
0
null
[ "license:cc-by-nc-sa-4.0", "region:us" ]
2023-11-28T12:41:24Z
2023-11-28T12:41:24.000Z
2023-11-28T12:41:24
--- license: cc-by-nc-sa-4.0 ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
Jaspernl/common_voice_13_0_nl_pseudo_labelled
Jaspernl
2023-11-28T13:50:06Z
0
0
null
[ "region:us" ]
2023-11-28T13:50:06Z
2023-11-28T12:45:19.000Z
2023-11-28T12:45:19
--- dataset_info: config_name: nl features: - name: client_id dtype: string - name: path dtype: string - name: audio dtype: audio: sampling_rate: 16000 - name: sentence dtype: string - name: up_votes dtype: int64 - name: down_votes dtype: int64 - name: age dtype: string - name: gender dtype: string - name: accent dtype: string - name: locale dtype: string - name: segment dtype: string - name: variant dtype: string - name: whisper_transcript sequence: int64 splits: - name: train num_bytes: 887412317.796 num_examples: 31906 - name: validation num_bytes: 355862437.37 num_examples: 10930 - name: test num_bytes: 402683280.568 num_examples: 10936 download_size: 1643910548 dataset_size: 1645958035.734 configs: - config_name: nl data_files: - split: train path: nl/train-* - split: validation path: nl/validation-* - split: test path: nl/test-* ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
tyzhu/find_sent_before_sent_train_100_eval_40_recite
tyzhu
2023-11-28T13:43:41Z
0
0
null
[ "region:us" ]
2023-11-28T13:43:41Z
2023-11-28T12:47:59.000Z
2023-11-28T12:47:59
--- 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: title dtype: string - name: context dtype: string splits: - name: train num_bytes: 1169584 num_examples: 644 - name: validation num_bytes: 377548 num_examples: 202 download_size: 325994 dataset_size: 1547132 --- # Dataset Card for "find_sent_before_sent_train_100_eval_40_recite" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.5445691347122192, -0.0738573893904686, 0.2889677882194519, 0.42903923988342285, -0.026656627655029297, -0.02416963130235672, 0.12088538706302643, 0.21919551491737366, 0.7557971477508545, 0.6391089558601379, -1.0631091594696045, -0.6634748578071594, -0.5230261087417603, -0.21797747910022...
null
null
null
null
null
null
null
null
null
null
null
null
null
tyzhu/find_sent_after_sent_train_100_eval_40_recite
tyzhu
2023-11-28T13:44:20Z
0
0
null
[ "region:us" ]
2023-11-28T13:44:20Z
2023-11-28T12:49:42.000Z
2023-11-28T12:49:42
--- 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: title dtype: string - name: context dtype: string splits: - name: train num_bytes: 1168154 num_examples: 644 - name: validation num_bytes: 377200 num_examples: 202 download_size: 325715 dataset_size: 1545354 --- # Dataset Card for "find_sent_after_sent_train_100_eval_40_recite" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.496530681848526, -0.008401576429605484, 0.3072666525840759, 0.4487752318382263, 0.004115242511034012, 0.02256515994668007, 0.09870839864015579, 0.1785963922739029, 0.7407034635543823, 0.5947513580322266, -0.9809296131134033, -0.599894106388092, -0.5363748669624329, -0.2411201447248459, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
tyzhu/find_sent_before_sent_train_200_eval_40_recite
tyzhu
2023-11-28T13:44:51Z
0
0
null
[ "region:us" ]
2023-11-28T13:44:51Z
2023-11-28T12:50:15.000Z
2023-11-28T12:50:15
--- 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: title dtype: string - name: context dtype: string splits: - name: train num_bytes: 2329316 num_examples: 1263 - name: validation num_bytes: 398956 num_examples: 203 download_size: 533740 dataset_size: 2728272 --- # Dataset Card for "find_sent_before_sent_train_200_eval_40_recite" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.5391755700111389, -0.0023822118528187275, 0.3294859230518341, 0.4412449896335602, -0.031510014086961746, 0.018736662343144417, 0.12890343368053436, 0.18120229244232178, 0.7011620402336121, 0.631971538066864, -1.0757534503936768, -0.6322876811027527, -0.5338778495788574, -0.2033138573169...
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null
null
null
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