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da745575b4499249aec1a87dd6161205630d3463 |
# Sentiment Analysis Dataset
This contains artificially constructed dataset labelled with their respective sentiment
## Dataset Description:
- Number of Rows: 10,000
- Number of Columns: 2
- Column Names: 'Tweet', 'Emotion'
- Description: This dataset contains tweets labeled with various emotions. Each row consists o... | nikesh66/sentiment-detection-dataset | [
"language:en",
"region:us"
] | 2023-12-11T10:56:51+00:00 | {"language": ["en"]} | 2023-12-11T11:23:07+00:00 | [] | [
"en"
] | TAGS
#language-English #region-us
|
# Sentiment Analysis Dataset
This contains artificially constructed dataset labelled with their respective sentiment
## Dataset Description:
- Number of Rows: 10,000
- Number of Columns: 2
- Column Names: 'Tweet', 'Emotion'
- Description: This dataset contains tweets labeled with various emotions. Each row consists o... | [
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43496510f20c4c3f0f18970f0160acf6cbaef442 |
# Hate Speech Dataset
This dataset contains artificially genrated tweets alongwith its label whether it is hatespeech or not
## Dataset Description
- Number of Rows: 5,000
- Number of Columns: 2
- Column Names: 'Tweet', 'Hate Speech'
- Description: This dataset comprises tweets with annotations indicating whether the... | nikesh66/Hatespeech-Dataset | [
"language:en",
"region:us"
] | 2023-12-11T11:11:14+00:00 | {"language": ["en"]} | 2023-12-11T11:13:41+00:00 | [] | [
"en"
] | TAGS
#language-English #region-us
|
# Hate Speech Dataset
This dataset contains artificially genrated tweets alongwith its label whether it is hatespeech or not
## Dataset Description
- Number of Rows: 5,000
- Number of Columns: 2
- Column Names: 'Tweet', 'Hate Speech'
- Description: This dataset comprises tweets with annotations indicating whether the... | [
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0c9bc18469ead579bbc540e4f765c1edaf07312c | # Slang Dataset
It contains artificially generated slang data along with their label
## Dataset Descripton:
- Number of Rows: 5,000
- Number of Columns: 2
- Column Names: 'Tweet', 'Sarcasm (yes/no)'
- Description: This dataset features tweets labeled for sarcasm. Each tweet is accompanied by a label ('yes' or 'no') i... | nikesh66/Slang-Dataset | [
"size_categories:1K<n<10K",
"language:en",
"region:us"
] | 2023-12-11T11:15:40+00:00 | {"language": ["en"], "size_categories": ["1K<n<10K"]} | 2023-12-11T11:18:32+00:00 | [] | [
"en"
] | TAGS
#size_categories-1K<n<10K #language-English #region-us
| # Slang Dataset
It contains artificially generated slang data along with their label
## Dataset Descripton:
- Number of Rows: 5,000
- Number of Columns: 2
- Column Names: 'Tweet', 'Sarcasm (yes/no)'
- Description: This dataset features tweets labeled for sarcasm. Each tweet is accompanied by a label ('yes' or 'no') i... | [
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a73648b5242e024dfc4b6ad23fe42df40533452f |
## SummEval FR
This dataset is a french translation of the original work [SummEval](https://github.com/Yale-LILY/SummEval).
The translation was made using [DeepL](https://www.deepl.com) from English to French.
We use this dataset for the french version of [MTEB](https://github.com/embeddings-benchmark/mteb) :
The... | lyon-nlp/summarization-summeval-fr-p2p | [
"task_categories:summarization",
"size_categories:n<1K",
"language:fr",
"license:apache-2.0",
"region:us"
] | 2023-12-11T11:17:49+00:00 | {"language": ["fr"], "license": "apache-2.0", "size_categories": ["n<1K"], "task_categories": ["summarization"]} | 2023-12-11T16:48:01+00:00 | [] | [
"fr"
] | TAGS
#task_categories-summarization #size_categories-n<1K #language-French #license-apache-2.0 #region-us
|
## SummEval FR
This dataset is a french translation of the original work SummEval.
The translation was made using DeepL from English to French.
We use this dataset for the french version of MTEB :
The annotations include summaries generated by 16 models from 100 source news articles (1600 examples in total). Each... | [
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426f9adc95648482d56d83a58fac80bc5e5ef813 |
# Sarcasm Dataset
This dataset contains sarcastic sentence along with their binary label
## Dataset Desciption:
- Number of Rows: 5,000
- Number of Columns: 2
- Column Names: 'Tweet', 'Slang (yes/no)'
- Description: The dataset contains tweets annotated for the use of slang. It includes a binary label ('yes' or 'no'... | nikesh66/Sarcasm-dataset | [
"size_categories:1K<n<10K",
"language:en",
"region:us"
] | 2023-12-11T11:21:07+00:00 | {"language": ["en"], "size_categories": ["1K<n<10K"]} | 2023-12-11T11:22:43+00:00 | [] | [
"en"
] | TAGS
#size_categories-1K<n<10K #language-English #region-us
|
# Sarcasm Dataset
This dataset contains sarcastic sentence along with their binary label
## Dataset Desciption:
- Number of Rows: 5,000
- Number of Columns: 2
- Column Names: 'Tweet', 'Slang (yes/no)'
- Description: The dataset contains tweets annotated for the use of slang. It includes a binary label ('yes' or 'no'... | [
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771b8b9a7c6743f6b327ecd5f3a6a40fd6b78c17 | # Dataset Card for "sys-human_db2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | collabteza/sys-human_db2 | [
"region:us"
] | 2023-12-11T11:31:52+00:00 | {"dataset_info": {"features": [{"name": "System Prompt", "dtype": "string"}, {"name": "Human Prompt", "dtype": "string"}, {"name": "Output", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 972089, "num_examples": 1530}], "download_size": 460352, "dataset_size": 972089}, "configs": [{"config_name": "defau... | 2023-12-11T11:31:53+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "sys-human_db2"
More Information needed | [
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a17d95c4af0a33a31591f187f1fe15232991397a | # Dataset Card for "raaga_dataset_v2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | zense-raaga-ai/raaga_dataset_v2 | [
"region:us"
] | 2023-12-11T11:42:23+00:00 | {"dataset_info": {"features": [{"name": "audio", "dtype": "audio"}, {"name": "RaagaNumber", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 22119715558.812, "num_examples": 86746}], "download_size": 29873744194, "dataset_size": 22119715558.812}} | 2023-12-11T13:30:39+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "raaga_dataset_v2"
More Information needed | [
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cb227a000b27d8db94198d1242e1607036136786 | # Dataset Card for Israel-HAMAS war news
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-... | aav-ds/Israel-HAMAS_war_news | [
"task_categories:text-classification",
"task_categories:text-generation",
"size_categories:10K<n<100K",
"language:en",
"region:us"
] | 2023-12-11T11:54:53+00:00 | {"language": ["en"], "size_categories": ["10K<n<100K"], "task_categories": ["text-classification", "text-generation"], "pretty_name": "Israel-HAMAS war news", "dataset_info": {"features": [{"name": "url", "dtype": "string"}, {"name": "datetime", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "text",... | 2023-12-11T19:24:26+00:00 | [] | [
"en"
] | TAGS
#task_categories-text-classification #task_categories-text-generation #size_categories-10K<n<100K #language-English #region-us
| # Dataset Card for Israel-HAMAS war news
## Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Dataset Creation
- Curation Rationale
- Source Data
- Personal and Sensitive Information
## Dataset ... | [
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ae6b0c54fca9fa26096f7de175c747e4b262e01a | # Dataset Card for Math-Shepherd
Project Page: [Math-Shepherd](https://rain-motion-6ec.notion.site/Math-Shepherd-A-Label-Free-Step-by-Step-Verifier-for-LLMs-in-Mathematical-Reasoning-41b6e73c860840e08697d347f8889bac#08e86c6d44c4452ba0b78c7aaea5f4f7)
Paper: https://arxiv.org/pdf/2312.08935.pdf
# Data Loading
```
from ... | peiyi9979/Math-Shepherd | [
"prm",
"synthesized data",
"arxiv:2312.08935",
"region:us"
] | 2023-12-11T12:04:14+00:00 | {"tags": ["prm", "synthesized data"]} | 2024-01-03T06:13:49+00:00 | [
"2312.08935"
] | [] | TAGS
#prm #synthesized data #arxiv-2312.08935 #region-us
| # Dataset Card for Math-Shepherd
Project Page: Math-Shepherd
Paper: URL
# Data Loading
# Data Instance
Every instance consists of three data fields: "input," "label," and "task".
1. "input": problem + step-by-step solution, e.g.,
2. "label": problem + step-by-step solution with automatic label, e.g.,
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605dfde55d1a10a685094c0706b9324f71236687 | # Dataset Card for "sys-human_db3"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | collabteza/sys-human_db3 | [
"region:us"
] | 2023-12-11T12:04:45+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}], "dataset_info": {"features": [{"name": "System Prompt", "dtype": "string"}, {"name": "Human Prompt", "dtype": "string"}, {"name": "Output", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 1092224, "num_e... | 2023-12-11T16:34:17+00:00 | [] | [] | TAGS
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62638c1f77a0842b630940aeb2a42f04572a2f40 | # Dataset Card for "voxpopuli_windows_cs"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | Predict9731/voxpopuli_windows_cs | [
"region:us"
] | 2023-12-11T12:19:28+00:00 | {"dataset_info": {"features": [{"name": "audio_id", "dtype": "string"}, {"name": "language", "dtype": {"class_label": {"names": {"0": "en", "1": "de", "2": "fr", "3": "es", "4": "pl", "5": "it", "6": "ro", "7": "hu", "8": "cs", "9": "nl", "10": "fi", "11": "hr", "12": "sk", "13": "sl", "14": "et", "15": "lt", "16": "en... | 2023-12-11T12:28:22+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "voxpopuli_windows_cs"
More Information needed | [
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185eb350a75261ca19f148f2100a1c9d925d9e1b |
# MT-Bench-French
This is a French version of [MT-Bench](https://arxiv.org/abs/2306.05685), created to evaluate the multi-turn conversation and instruction-following capabilities of LLMs. Similar to its original version, MT-Bench-French comprises 80 high-quality, multi-turn questions spanning eight main categories.
... | bofenghuang/mt-bench-french | [
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"size_categories:n<1K",
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"license:apache-2.0",
"evaluation",
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"region:us"
] | 2023-12-11T13:01:43+00:00 | {"language": ["fr"], "license": "apache-2.0", "size_categories": ["n<1K"], "task_categories": ["question-answering", "conversational"], "pretty_name": "MT-Bench-French", "tags": ["evaluation"], "configs": [{"config_name": "default", "data_files": [{"split": "test", "path": "question.jsonl"}]}]} | 2024-01-26T10:14:19+00:00 | [
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|
# MT-Bench-French
This is a French version of MT-Bench, created to evaluate the multi-turn conversation and instruction-following capabilities of LLMs. Similar to its original version, MT-Bench-French comprises 80 high-quality, multi-turn questions spanning eight main categories.
All questions have undergone transla... | [
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77251b39a4d5b7e0027a2c70921b9fef30d20947 |
# Dataset Card for Evaluation run of Deci/DeciLM-7B
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/Deci/DeciLM-7B
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** clementine@hf.co
### Dataset Summary
Dataset ... | open-llm-leaderboard/details_Deci__DeciLM-7B | [
"region:us"
] | 2023-12-11T13:08:44+00:00 | {"pretty_name": "Evaluation run of Deci/DeciLM-7B", "dataset_summary": "Dataset automatically created during the evaluation run of model [Deci/DeciLM-7B](https://huggingface.co/Deci/DeciLM-7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\nThe dataset is composed of ... | 2023-12-12T13:55:39+00:00 | [] | [] | TAGS
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|
# Dataset Card for Evaluation run of Deci/DeciLM-7B
## Dataset Description
- Homepage:
- Repository: URL
- Paper:
- Leaderboard: URL
- Point of Contact: clementine@URL
### Dataset Summary
Dataset automatically created during the evaluation run of model Deci/DeciLM-7B on the Open LLM Leaderboard.
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061f89a5bc4c64870aaa1c268dd854b19fb1afc1 |
# UltraFeedback - Multi-Binarized using the Average of Preference Ratings (Cleaned)
This dataset represents a new iteration on top of [`argilla/ultrafeedback-binarized-preferences-cleaned`](https://huggingface.co/datasets/argilla/ultrafeedback-binarized-preferences-cleaned),
and has been created to explore whether DP... | argilla/ultrafeedback-multi-binarized-preferences-cleaned | [
"task_categories:text-generation",
"size_categories:100K<n<1M",
"language:en",
"license:mit",
"dpo",
"preference",
"ultrafeedback",
"region:us"
] | 2023-12-11T14:04:24+00:00 | {"language": ["en"], "license": "mit", "size_categories": ["100K<n<1M"], "task_categories": ["text-generation"], "pretty_name": "UltraFeedback Multi-Binarized Preferences Cleaned", "dataset_info": {"features": [{"name": "source", "dtype": "string"}, {"name": "prompt", "dtype": "string"}, {"name": "chosen", "list": [{"n... | 2023-12-11T14:21:14+00:00 | [] | [
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|
# UltraFeedback - Multi-Binarized using the Average of Preference Ratings (Cleaned)
This dataset represents a new iteration on top of 'argilla/ultrafeedback-binarized-preferences-cleaned',
and has been created to explore whether DPO fine-tuning with more than one rejection per chosen response helps the model perform ... | [
"# UltraFeedback - Multi-Binarized using the Average of Preference Ratings (Cleaned)\n\nThis dataset represents a new iteration on top of 'argilla/ultrafeedback-binarized-preferences-cleaned',\nand has been created to explore whether DPO fine-tuning with more than one rejection per chosen response helps the model p... | [
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db3f2582c3d4219059f00b650f68968486034aee | # Dataset Card for "librispeech_asr-audiodec_44k"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | anthony-wss/librispeech_asr-audiodec_44k | [
"region:us"
] | 2023-12-11T14:11:39+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "train.clean.360", "path": "data/train.clean.360-*"}, {"split": "train.other.500", "path": "data/train.other.500-*"}]}], "dataset_info": {"features": [{"name": "text", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "unit", "sequence": {"s... | 2023-12-13T04:31:36+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "librispeech_asr-audiodec_44k"
More Information needed | [
"# Dataset Card for \"librispeech_asr-audiodec_44k\"\n\nMore Information needed"
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aebfdb54dcbdb99dc0ef6b2e85f7d2237957acde | # Can It Edit? Evaluating the Ability of Large Language Models to Follow Code Editing Instructions
CanItEdit is a benchmark for evaluating LLMs on instructional code editing, the task of updating a program given a natural language instruction. The benchmark contains 54 hand-crafted Python programs with before and after... | nuprl/CanItEdit | [
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"size_categories:n<1K",
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"language:en",
"license:mit",
"code-generation",
"region:us"
] | 2023-12-11T14:13:35+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["expert-generated"], "language": ["en"], "license": ["mit"], "multilinguality": ["monolingual"], "size_categories": ["n<1K"], "source_datasets": ["original"], "task_categories": ["text2text-generation"], "task_ids": [], "paperswithcode_id": "canitedit... | 2023-12-14T20:57:48+00:00 | [] | [
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| # Can It Edit? Evaluating the Ability of Large Language Models to Follow Code Editing Instructions
CanItEdit is a benchmark for evaluating LLMs on instructional code editing, the task of updating a program given a natural language instruction. The benchmark contains 54 hand-crafted Python programs with before and after... | [
"# Can It Edit? Evaluating the Ability of Large Language Models to Follow Code Editing Instructions\nCanItEdit is a benchmark for evaluating LLMs on instructional code editing, the task of updating a program given a natural language instruction. The benchmark contains 54 hand-crafted Python programs with before and... | [
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18c319deef96d0b0af2702a8f99c38b1ea37a41c | # Dataset Card for "Alis"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | ArasAyen/Alis | [
"region:us"
] | 2023-12-11T14:14:53+00:00 | {"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 974600521.0, "num_examples": 659}], "download_size": 974328268, "dataset_size": 974600521.0}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path... | 2023-12-11T14:15:38+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "Alis"
More Information needed | [
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eb407d5702e518776bd3cad5959c610b139e16dc | ### dataset source
excellent sharing：
https://github.com/cbaziotis/datastories-semeval2017-task4/tree/master/dataset/Subtask_A/4A-English
task government：
https://alt.qcri.org/semeval2017/task4/index.php?id=data-and-tools | Siki-77/twitter2017 | [
"license:apache-2.0",
"region:us"
] | 2023-12-11T14:18:59+00:00 | {"license": "apache-2.0"} | 2023-12-17T09:03:49+00:00 | [] | [] | TAGS
#license-apache-2.0 #region-us
| ### dataset source
excellent sharing：
URL
task government：
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13ac0a9c60d115274592c54f5c69fdadcd782e23 | WARNING: EXTREMELY WORK IN PROGRESS. NOT YET USEABLE; HAVENT REMOVED RLHF INSTANCES YET. | unaidedelf87777/slimorca-sem_deduped | [
"region:us"
] | 2023-12-11T14:27:52+00:00 | {"dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "system_message", "dtype": "string"}, {"name": "instruction", "dtype": "string"}, {"name": "completion", "dtype": "string"}, {"name": "meta", "struct": [{"name": "topic_depth_1", "dtype": "string"}, {"name": "topic_depth_2", "dtype": "string"}, ... | 2023-12-12T17:46:46+00:00 | [] | [] | TAGS
#region-us
| WARNING: EXTREMELY WORK IN PROGRESS. NOT YET USEABLE; HAVENT REMOVED RLHF INSTANCES YET. | [] | [
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4696f11b9c3746aa5877d8e114eaf449f78b131d |
# Dataset Card for openslr-slr69-ca-denoised
This is a post-processed version of the Catalan subset belonging to the [Open Speech and Language Resources (OpenSLR)](https://www.openslr.org/index.html) speech dataset.
Specifically the subset [OpenSLR-69](https://www.openslr.org/69).
The original HF🤗 SLR-69 dataset ... | projecte-aina/openslr-slr69-ca-trimmed-denoised | [
"task_categories:text-to-speech",
"annotations_creators:no-annotation",
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"arxiv:2202.07790",
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] | 2023-12-11T14:43:28+00:00 | {"annotations_creators": ["no-annotation"], "language_creators": ["crowdsourced"], "language": ["ca"], "license": ["cc-by-sa-4.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": "openslr", "task_categories": ["text-to-speech"], "task_ids": [], "pretty_name": "openslr-slr69-ca-t... | 2024-01-17T17:00:46+00:00 | [
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|
# Dataset Card for openslr-slr69-ca-denoised
This is a post-processed version of the Catalan subset belonging to the Open Speech and Language Resources (OpenSLR) speech dataset.
Specifically the subset OpenSLR-69.
The original HF SLR-69 dataset is located here.
Same license is maintained: Attribution-ShareAlike 4... | [
"# Dataset Card for openslr-slr69-ca-denoised\n\nThis is a post-processed version of the Catalan subset belonging to the Open Speech and Language Resources (OpenSLR) speech dataset. \nSpecifically the subset OpenSLR-69. \n\nThe original HF SLR-69 dataset is located here.\n\nSame license is maintained: Attribution-S... | [
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cd58f5fcb9e75bdc3e121726695d76b2c14b36ee |
### Description
This dataset is derived from the already existing dataset made by AI4Bharat. We have used the [IndicXParaphrase](https://huggingface.co/datasets/ai4bharat/IndicXParaphrase) dataset of AI4Bharat to create this instruction style dataset.
We have used the malayalam split of the above mentioned dataset t... | el2e10/aya-paraphrase-malayalam | [
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"size_categories:n<1K",
"source_datasets:extended|ai4bharat/IndicXParaphrase",
"language:ml",
"license:cc",
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] | 2023-12-11T14:48:09+00:00 | {"language": ["ml"], "license": "cc", "size_categories": ["n<1K"], "source_datasets": ["extended|ai4bharat/IndicXParaphrase"], "task_categories": ["text-generation"], "pretty_name": "Aya Paraphrase Malayalam", "dataset_info": {"features": [{"name": "inputs", "dtype": "string"}, {"name": "targets", "dtype": "string"}, {... | 2024-01-26T14:14:25+00:00 | [] | [
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#task_categories-text-generation #size_categories-n<1K #source_datasets-extended|ai4bharat/IndicXParaphrase #language-Malayalam #license-cc #region-us
|
### Description
This dataset is derived from the already existing dataset made by AI4Bharat. We have used the IndicXParaphrase dataset of AI4Bharat to create this instruction style dataset.
We have used the malayalam split of the above mentioned dataset to create this one. This was created as part of Aya Open Scienc... | [
"### Description\n\nThis dataset is derived from the already existing dataset made by AI4Bharat. We have used the IndicXParaphrase dataset of AI4Bharat to create this instruction style dataset. \nWe have used the malayalam split of the above mentioned dataset to create this one. This was created as part of Aya Open... | [
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bb75aa9036dadcfa4051cf6be6e7671fead14599 | # Livre des procédures fiscales, non-instruct (11-12-2023)
This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for tax practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusti... | lemoneresearch/lpf | [
"task_categories:text-generation",
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"language:fr",
"license:apache-2.0",
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"tax"... | 2023-12-11T14:50:04+00:00 | {"language": ["fr"], "license": "apache-2.0", "multilinguality": ["monolingual"], "size_categories": ["n<1K"], "source_datasets": ["original"], "task_categories": ["text-generation", "table-question-answering", "summarization", "conversational"], "pretty_name": "Livre des proc\u00e9dures fiscales (LPF)", "tags": ["fine... | 2023-12-11T14:50:55+00:00 | [] | [
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This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for tax practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusti... | [
"# Livre des procédures fiscales, non-instruct (11-12-2023)\n\nThis project focuses on fine-tuning pre-trained language models to create efficient and accurate models for tax practice. \n\nFine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involve... | [
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6d91d812bf4eef93eb55687483fdb7bdbc1e4821 | # Dataset Card for "EUIPO_QA"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | agil/EUIPO_QA | [
"region:us"
] | 2023-12-11T14:51:44+00:00 | {"dataset_info": {"features": [{"name": "ID", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "source", "dtype": "string"}, {"name": "answer", "dtype": "string"}, {"name": "category", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 145159.30633802817, "num_examples": 227}, {"name": "... | 2024-01-11T21:56:30+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "EUIPO_QA"
More Information needed | [
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b6e602ed7e1ce9f89d150301ae8fe68b541ba946 | # Code Général des Impôts, non-instruct (11-12-2023)
This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for tax practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the... | lemoneresearch/cgi | [
"task_categories:text-generation",
"task_categories:table-question-answering",
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"source_datasets:original",
"language:fr",
"license:apache-2.0",
"finetuning",
"legal",
"... | 2023-12-11T14:55:01+00:00 | {"language": ["fr"], "license": "apache-2.0", "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-generation", "table-question-answering", "summarization", "conversational"], "pretty_name": "Code G\u00e9n\u00e9ral des Imp\u00f4ts (CGI)", "tags"... | 2023-12-11T14:55:57+00:00 | [] | [
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This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for tax practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the... | [
"# Code Général des Impôts, non-instruct (11-12-2023)\n\nThis project focuses on fine-tuning pre-trained language models to create efficient and accurate models for tax practice. \n\nFine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adju... | [
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85fefb51eb3df1a8e8ad2c5b6d85008b09deba47 |
# QUORA_ONE_MANY_QA
This dataset is derived from **quora.com** questioning data. It is a question with multiple answers.
# STATISTICS
- 902-1000000 12.5G
- Updating... | LxYxvv/quora_qa | [
"task_categories:question-answering",
"license:mit",
"region:us"
] | 2023-12-11T14:56:52+00:00 | {"license": "mit", "task_categories": ["question-answering"]} | 2024-02-17T06:54:41+00:00 | [] | [] | TAGS
#task_categories-question-answering #license-mit #region-us
|
# QUORA_ONE_MANY_QA
This dataset is derived from URL questioning data. It is a question with multiple answers.
# STATISTICS
- 902-1000000 12.5G
- Updating... | [
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"passage: TAGS\n#task_categories-question-answering #license-mit #region-us \n# QUORA_ONE_MANY_QA\nThis dataset is derived from URL questioning data. It is a question with multiple answers.# STATISTICS\n- 902-1000000 12.5G\n- Updating..."
] |
65fad0b49c0f3e54453f37a0e37ebbe2a7cac76e |
# 🏟️ Long Code Arena (Code Editing)
This is the benchmark for Code Editing task as part of
🏟️ [Long Code Arena benchmark](https://huggingface.co/spaces/JetBrains-Research/long-code-arena).
## How-to
> Temporary: While the dataset is private, if you haven't used HF Hub before, add your token via `huggingface-cli`
... | JetBrains-Research/lca-code-editing | [
"region:us"
] | 2023-12-11T15:03:37+00:00 | {"dataset_info": [{"config_name": "commitchronicle-py-long", "features": [{"name": "hash", "dtype": "string"}, {"name": "repo", "dtype": "string"}, {"name": "date", "dtype": "string"}, {"name": "license", "dtype": "string"}, {"name": "message", "dtype": "string"}, {"name": "mods", "list": [{"name": "change_type", "dtyp... | 2024-01-10T15:41:44+00:00 | [] | [] | TAGS
#region-us
| ️ Long Code Arena (Code Editing)
================================
This is the benchmark for Code Editing task as part of
️ Long Code Arena benchmark.
How-to
------
>
> Temporary: While the dataset is private, if you haven't used HF Hub before, add your token via 'huggingface-cli'
> first:
>
>
>
1. List all... | [
"### Full data\n\n\nThis section concerns configuration with *full data* about each commit (no '-labels' suffix).\n\n\nEach example has the following fields:\n\n\n\nEach file modification has the following fields:\n\n\n\nData point example:",
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26b11d70e8cd47e93519f0c5b9871a2ef01a241d | # Livre des procédures fiscales, non-instruct (11-12-2023)
This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for tax practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusti... | louisbrulenaudet/lpf | [
"task_categories:text-generation",
"task_categories:table-question-answering",
"task_categories:summarization",
"task_categories:conversational",
"multilinguality:monolingual",
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"source_datasets:original",
"language:fr",
"license:apache-2.0",
"finetuning",
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"tax"... | 2023-12-11T15:11:08+00:00 | {"language": ["fr"], "license": "apache-2.0", "multilinguality": ["monolingual"], "size_categories": ["n<1K"], "source_datasets": ["original"], "task_categories": ["text-generation", "table-question-answering", "summarization", "conversational"], "pretty_name": "Livre des proc\u00e9dures fiscales (LPF)", "tags": ["fine... | 2023-12-11T15:12:01+00:00 | [] | [
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This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for tax practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusti... | [
"# Livre des procédures fiscales, non-instruct (11-12-2023)\n\nThis project focuses on fine-tuning pre-trained language models to create efficient and accurate models for tax practice. \n\nFine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involve... | [
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d5628f045420f213017b5b71deff77f1406fdbee | # Code Général des Impôts, non-instruct (11-12-2023)
This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for tax practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the... | louisbrulenaudet/cgi | [
"task_categories:text-generation",
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"task_categories:summarization",
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"language:fr",
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"... | 2023-12-11T15:12:43+00:00 | {"language": ["fr"], "license": "apache-2.0", "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-generation", "table-question-answering", "summarization", "conversational"], "pretty_name": "Code G\u00e9n\u00e9ral des Imp\u00f4ts (CGI)", "tags"... | 2023-12-11T15:13:33+00:00 | [] | [
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This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for tax practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the... | [
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46b2b8ca5fe89ef9776bbb2673c934f101f801b8 |
## Truthy DPO
This is a dataset designed to enhance the overall truthfulness of LLMs, without sacrificing immersion when roleplaying as a human.
For example, in normal AI assistant model, the model should not try to describe what the warmth of the sun feels like, but if the system prompt indicates it's a human, it s... | jondurbin/truthy-dpo-v0.1 | [
"license:cc-by-4.0",
"region:us"
] | 2023-12-11T15:34:04+00:00 | {"license": "cc-by-4.0"} | 2024-01-11T10:19:14+00:00 | [] | [] | TAGS
#license-cc-by-4.0 #region-us
|
## Truthy DPO
This is a dataset designed to enhance the overall truthfulness of LLMs, without sacrificing immersion when roleplaying as a human.
For example, in normal AI assistant model, the model should not try to describe what the warmth of the sun feels like, but if the system prompt indicates it's a human, it s... | [
"## Truthy DPO\n\nThis is a dataset designed to enhance the overall truthfulness of LLMs, without sacrificing immersion when roleplaying as a human.\n\nFor example, in normal AI assistant model, the model should not try to describe what the warmth of the sun feels like, but if the system prompt indicates it's a hum... | [
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92712e086d4099c1f05be6a6e02439bf2f2d9f2f |
## Toxic-DPO
This is a highly toxic, "harmful" dataset meant to illustrate how DPO can be used to de-censor/unalign a model quite easily using direct-preference-optimization (DPO) using very few examples.
Most of the examples still contain some amount of warnings/disclaimers, so it's still somewhat editorialized.
#... | unalignment/toxic-dpo-v0.1 | [
"license:cc-by-4.0",
"not-for-all-audiences",
"region:us"
] | 2023-12-11T15:51:16+00:00 | {"license": "cc-by-4.0", "tags": ["not-for-all-audiences"]} | 2023-12-26T18:08:07+00:00 | [] | [] | TAGS
#license-cc-by-4.0 #not-for-all-audiences #region-us
|
## Toxic-DPO
This is a highly toxic, "harmful" dataset meant to illustrate how DPO can be used to de-censor/unalign a model quite easily using direct-preference-optimization (DPO) using very few examples.
Most of the examples still contain some amount of warnings/disclaimers, so it's still somewhat editorialized.
#... | [
"## Toxic-DPO\n\nThis is a highly toxic, \"harmful\" dataset meant to illustrate how DPO can be used to de-censor/unalign a model quite easily using direct-preference-optimization (DPO) using very few examples.\n\nMost of the examples still contain some amount of warnings/disclaimers, so it's still somewhat editori... | [
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9ccdd2aa175ba4b2e23824bf1526faa5f0eb209a | # Dataset Card for "bash_images_2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | SpongeBash/bash_images_2 | [
"region:us"
] | 2023-12-11T16:03:41+00:00 | {"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 146725.0, "num_examples": 12}], "download_size": 148375, "dataset_size": 146725.0}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/t... | 2023-12-11T16:03:43+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "bash_images_2"
More Information needed | [
"# Dataset Card for \"bash_images_2\"\n\nMore Information needed"
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58cdc294fe2b5356afca2770ec921fd88b31c397 |
# Dataset Card for Evaluation run of Deci/DeciLM-7B-instruct
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/Deci/DeciLM-7B-instruct
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** clementine@hf.co
### Dataset... | open-llm-leaderboard/details_Deci__DeciLM-7B-instruct | [
"region:us"
] | 2023-12-11T16:07:38+00:00 | {"pretty_name": "Evaluation run of Deci/DeciLM-7B-instruct", "dataset_summary": "Dataset automatically created during the evaluation run of model [Deci/DeciLM-7B-instruct](https://huggingface.co/Deci/DeciLM-7B-instruct) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\n... | 2023-12-12T13:57:39+00:00 | [] | [] | TAGS
#region-us
|
# Dataset Card for Evaluation run of Deci/DeciLM-7B-instruct
## Dataset Description
- Homepage:
- Repository: URL
- Paper:
- Leaderboard: URL
- Point of Contact: clementine@URL
### Dataset Summary
Dataset automatically created during the evaluation run of model Deci/DeciLM-7B-instruct on the Open LLM Leaderboard... | [
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b07750e89b08a9dcebf211eff42d2fe2c846a78f | # Dataset Card for "ML2021_ASR_ST"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | ky552/ML2021_ASR_ST | [
"region:us"
] | 2023-12-11T16:14:38+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}], "dataset_info": {"features": [{"name": "audio", "dtype": {"audio": {"sampling_rate": 16000}}}, {"name": "transcription", "dtype": "strin... | 2023-12-11T16:44:07+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "ML2021_ASR_ST"
More Information needed | [
"# Dataset Card for \"ML2021_ASR_ST\"\n\nMore Information needed"
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d75aba1981c74510be1f985a49a3be342168b5f6 | # Dataset Card for "hugging_face"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | SpongeBash/hugging_face | [
"region:us"
] | 2023-12-11T16:55:14+00:00 | {"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 75931.0, "num_examples": 12}], "download_size": 77302, "dataset_size": 75931.0}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/trai... | 2023-12-11T16:55:16+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "hugging_face"
More Information needed | [
"# Dataset Card for \"hugging_face\"\n\nMore Information needed"
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1a137832c78f2a18978023263dbbbbde60b9802b | Categorization and Segregation, version1:
- Bucket 1 Allocation:
- If the Petri dish contains P. aeruginosa and/or E. coli colonies.
- Bucket 2 Allocation:
- If the Petri dish contains S. aureus and B. subtilis colonies.
- Bucket 3 Allocation:
- For Petri dishes containing colonies other than the specified typ... | adamrian/petri-dish | [
"region:us"
] | 2023-12-11T17:01:20+00:00 | {} | 2023-12-12T02:05:40+00:00 | [] | [] | TAGS
#region-us
| Categorization and Segregation, version1:
- Bucket 1 Allocation:
- If the Petri dish contains P. aeruginosa and/or E. coli colonies.
- Bucket 2 Allocation:
- If the Petri dish contains S. aureus and B. subtilis colonies.
- Bucket 3 Allocation:
- For Petri dishes containing colonies other than the specified typ... | [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
83b847cefc8014eb2b1136403664ee2e71268d1b | # Dataset Card for "mscoco_simplified_falcon"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | BubbleJoe/mscoco_simplified_falcon | [
"region:us"
] | 2023-12-11T17:40:41+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "restval", "path": "data/restval-*"}, {"split": "validation", "path": "data/validation-*"}, {"split": "test", "path": "data/test-*"}]}], "dataset_info": {"features": [{"name": "sentids", "dtype": "int64"}, {"nam... | 2023-12-12T21:43:47+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "mscoco_simplified_falcon"
More Information needed | [
"# Dataset Card for \"mscoco_simplified_falcon\"\n\nMore Information needed"
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"TAGS\n#region-us \n",
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eedaf9060827b052204c0d854d8a39172dc74ba9 | # Dataset Card for "hoopers"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | ppower1/hoopers | [
"region:us"
] | 2023-12-11T17:44:49+00:00 | {"dataset_info": {"features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 17775, "num_examples": 100}], "download_size": 3106, "dataset_size": 17775}} | 2023-12-11T17:53:13+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "hoopers"
More Information needed | [
"# Dataset Card for \"hoopers\"\n\nMore Information needed"
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"TAGS\n#region-us \n",
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"passage: TAGS\n#region-us \n# Dataset Card for \"hoopers\"\n\nMore Information needed"
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e8423695c7a4f5dc326d0ae5d92b934747c358f5 |
This is a WIP dataset used to identify Prompt injections. This dataset contains legitimate prompts and jailbreak prompts. It also contains combinations of phrases that could potentially be used to jailbreak llms
inspired from the [rebuff project](https://www.rebuff.ai).
Reference:
1. [jailbreakchat](https://www.jai... | predictionguard/promptinjections | [
"license:mit",
"region:us"
] | 2023-12-11T17:48:07+00:00 | {"license": "mit", "dataset_info": {"features": [{"name": "prompt", "dtype": "string"}, {"name": "INJECTION", "dtype": "bool"}, {"name": "Unnamed: 0", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 5879405, "num_examples": 17678}], "download_size": 3168127, "dataset_size": 5879405}, "configs": [{"config_... | 2023-12-13T14:16:20+00:00 | [] | [] | TAGS
#license-mit #region-us
|
This is a WIP dataset used to identify Prompt injections. This dataset contains legitimate prompts and jailbreak prompts. It also contains combinations of phrases that could potentially be used to jailbreak llms
inspired from the rebuff project.
Reference:
1. jailbreakchat
2. Srikanth Srinivas. (2023). URL Dataset.... | [] | [
"TAGS\n#license-mit #region-us \n"
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11
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f91ee0f9df1d1f1d784e5240ea61291c50ececf7 | # Dataset Card for "semeval-task-8-a-mono-v2-test-paraphrase-2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | kpriyanshu256/semeval-task-8-a-mono-v2-test-paraphrase-2 | [
"region:us"
] | 2023-12-11T18:06:38+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "test", "path": "data/test-*"}]}], "dataset_info": {"features": [{"name": "text", "dtype": "string"}, {"name": "label", "dtype": "int64"}, {"name": "model", "dtype": "string"}, {"name": "source", "dtype": "string"}, {"name": "id", "dtype": "int64"}, {"nam... | 2023-12-11T18:06:39+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "semeval-task-8-a-mono-v2-test-paraphrase-2"
More Information needed | [
"# Dataset Card for \"semeval-task-8-a-mono-v2-test-paraphrase-2\"\n\nMore Information needed"
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16af2ad182b956e94b1beefbfef1c3bf6084dce2 |
# Dataset Card for Evaluation run of mistralai/Mixtral-8x7B-v0.1
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) on the [Open LLM Leaderboard](https://huggingface.co/spa... | open-llm-leaderboard/details_mistralai__Mixtral-8x7B-v0.1 | [
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# Dataset Card for Evaluation run of mistralai/Mixtral-8x7B-v0.1
Dataset automatically created during the evaluation run of model mistralai/Mixtral-8x7B-v0.1 on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created f... | [
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782ceaaeb7f01c47e80cfdcf61a577ce01942fa2 | # Dataset Card for "semeval-task-8-a-mono-v2-test-paraphrase-2-mistral-7b"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | kpriyanshu256/semeval-task-8-a-mono-v2-test-paraphrase-2-mistral-7b | [
"region:us"
] | 2023-12-11T18:38:24+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "test", "path": "data/test-*"}]}], "dataset_info": {"features": [{"name": "text", "dtype": "string"}, {"name": "label", "dtype": "int64"}, {"name": "model", "dtype": "string"}, {"name": "source", "dtype": "string"}, {"name": "id", "dtype": "int64"}, {"nam... | 2023-12-11T18:38:26+00:00 | [] | [] | TAGS
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| # Dataset Card for "semeval-task-8-a-mono-v2-test-paraphrase-2-mistral-7b"
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56763b13c50307c9ef2f286264178a53525b72b3 | Dataset from: https://huggingface.co/datasets/glue
Every split besides the ax split is in this dataset.
Lines above 512 characters from the BERT-cased (bert-base-cased) tokenizer are removed | gmongaras/BERT_Base_Cased_512_GLUE | [
"region:us"
] | 2023-12-11T18:54:49+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "validation", "path": "data/validation-*"}, {"split": "test", "path": "data/test-*"}]}], "dataset_info": {"features": [{"name": "sentence", "dtype": "string"}, {"name": "label", "dtype": "float64"}, {"name": "da... | 2023-12-11T19:27:11+00:00 | [] | [] | TAGS
#region-us
| Dataset from: URL
Every split besides the ax split is in this dataset.
Lines above 512 characters from the BERT-cased (bert-base-cased) tokenizer are removed | [] | [
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40c8a062005684f623bd70f6be511e6ba11da952 | ### Dataset Summary
This dataset consists of 3570 tweets, which were manually labeled as cyberbullying or not cyberbullying. A distinguishing feature of this dataset is that for a given word, there is an annotated tweet labeled as cyberbullying that contains that word, and another tweet labeled as not cyberbullying wi... | FelipeGuerra/Colombian_Spanish_Cyberbullying_Dataset_1 | [
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#license-mit #region-us
| ### Dataset Summary
This dataset consists of 3570 tweets, which were manually labeled as cyberbullying or not cyberbullying. A distinguishing feature of this dataset is that for a given word, there is an annotated tweet labeled as cyberbullying that contains that word, and another tweet labeled as not cyberbullying wi... | [
"### Dataset Summary\n\nThis dataset consists of 3570 tweets, which were manually labeled as cyberbullying or not cyberbullying. A distinguishing feature of this dataset is that for a given word, there is an annotated tweet labeled as cyberbullying that contains that word, and another tweet labeled as not cyberbull... | [
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8bae46bba9bd71b7bed965988814e7334a07fec2 | # Code des douanes, non-instruct (11-12-2023)
This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the mode... | louisbrulenaudet/code-douanes | [
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"... | 2023-12-11T19:08:27+00:00 | {"language": ["fr"], "license": "apache-2.0", "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-generation", "table-question-answering", "summarization", "conversational"], "pretty_name": "Code des douanes", "tags": ["finetuning", "legal", "f... | 2023-12-12T10:43:48+00:00 | [] | [
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bd37158db078224c2cf47488d81624ccabf3dc02 | # Code de la consommation, non-instruct (11-12-2023)
This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting t... | louisbrulenaudet/code-consommation | [
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eb56aab0d9eecc8d9087901ab0f55fbe07ca91fe | ### Dataset Summary
This dataset consists of 2566 tweets and maintains a balanced distribution between cyberbullying and not cyberbullying. For every keyword or phrase, there is an annotated tweet labeled as cyberbullying that contains that word or phrase.
The not cyberbullying category predominantly includes tweets ... | FelipeGuerra/Colombian_Spanish_Cyberbullying_Dataset_2 | [
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#license-mit #region-us
| ### Dataset Summary
This dataset consists of 2566 tweets and maintains a balanced distribution between cyberbullying and not cyberbullying. For every keyword or phrase, there is an annotated tweet labeled as cyberbullying that contains that word or phrase.
The not cyberbullying category predominantly includes tweets ... | [
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c6074d453ebb525effc750edca60cbfebb77cbd9 | Original Dataset from: https://huggingface.co/datasets/glue
This dataset is adapted from https://huggingface.co/datasets/gmongaras/BERT_Base_Cased_512_GLUE
Every split besides the ax split is in this dataset.
Lines above 512 tokens from the BERT-cased (bert-base-cased) tokenizer are removed in the original dataset
... | gmongaras/BERT_Base_Cased_512_GLUE_Mapped | [
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#region-us
| Original Dataset from: URL
This dataset is adapted from URL
Every split besides the ax split is in this dataset.
Lines above 512 tokens from the BERT-cased (bert-base-cased) tokenizer are removed in the original dataset
If in any case the sentences are longer than 512 tokens, they are subsetted.
Original labels an... | [] | [
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22d33393fefe6a2cb9f4cde5beebfba995a5576d |
## Dataset Summary
This is the training data of the model `Propositionizer-wiki`. We prompt GPT-4 to decompose a Wikipedia paragraph into a list of propositions.
We propose this training data to explore the concept of propositions as retrieval units. The propositions are defined as follows:
1. Each proposition shou... | chentong00/propositionizer-wiki-data | [
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"region:us"
] | 2023-12-11T20:37:47+00:00 | {"license": "apache-2.0", "size_categories": ["10K<n<100K"], "task_categories": ["text2text-generation"]} | 2023-12-11T21:51:06+00:00 | [] | [] | TAGS
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## Dataset Summary
This is the training data of the model 'Propositionizer-wiki'. We prompt GPT-4 to decompose a Wikipedia paragraph into a list of propositions.
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5a375b31b60b7d6604e8b400ee2070e346412d33 | ---
task_categories:
- question-answering
- summarization
+ - zero-shot-classification
language:
- en
- el
size_categories:
- 10K<n<100K
+ --- | dimitristzel/Diploma | [
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| ---
task_categories:
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language:
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size_categories:
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c364b3ed81dfc0f1fbb9e231f4ef1f6c7a3b42e3 |
# Dataset Card for Evaluation run of v1olet/v1olet_marcoroni-go-bruins-merge-7B
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [v1olet/v1olet_marcoroni-go-bruins-merge-7B](https://huggingface.co/v1olet/v1olet_marcoroni-go-bruins-merge-7B) on the [Ope... | open-llm-leaderboard/details_v1olet__v1olet_marcoroni-go-bruins-merge-7B | [
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] | 2023-12-11T22:22:57+00:00 | {"pretty_name": "Evaluation run of v1olet/v1olet_marcoroni-go-bruins-merge-7B", "dataset_summary": "Dataset automatically created during the evaluation run of model [v1olet/v1olet_marcoroni-go-bruins-merge-7B](https://huggingface.co/v1olet/v1olet_marcoroni-go-bruins-merge-7B) on the [Open LLM Leaderboard](https://huggi... | 2023-12-11T22:23:42+00:00 | [] | [] | TAGS
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# Dataset Card for Evaluation run of v1olet/v1olet_marcoroni-go-bruins-merge-7B
Dataset automatically created during the evaluation run of model v1olet/v1olet_marcoroni-go-bruins-merge-7B on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
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629e12e224cbab2a355b645198d66ac4e5e7fb91 |
# Dataset Card for Evaluation run of Toten5/Marcoroni-v3-neural-chat-v3-3-Slerp
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Toten5/Marcoroni-v3-neural-chat-v3-3-Slerp](https://huggingface.co/Toten5/Marcoroni-v3-neural-chat-v3-3-Slerp) on the [Ope... | open-llm-leaderboard/details_Toten5__Marcoroni-v3-neural-chat-v3-3-Slerp | [
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# Dataset Card for Evaluation run of Toten5/Marcoroni-v3-neural-chat-v3-3-Slerp
Dataset automatically created during the evaluation run of model Toten5/Marcoroni-v3-neural-chat-v3-3-Slerp on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
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f11ff2d2b8d9bc96365dcb164e502c119697b4bb | # Dataset Card for "counterfactual_babylm_aann_indef_anan"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | kanishka/counterfactual_babylm_aann_indef_anan | [
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| # Dataset Card for "counterfactual_babylm_aann_indef_anan"
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6f55b37695bd5e7f210184d42f8d1c615fa6bdd1 | # Dataset Card for "counterfactual_babylm_aann_all_det_anan"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | kanishka/counterfactual_babylm_aann_all_det_anan | [
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#region-us
| # Dataset Card for "counterfactual_babylm_aann_all_det_anan"
More Information needed | [
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73d3fb4732b7e1a58bc3c9da158e9be24656faf8 | # Dataset Card for "counterfactual_babylm_aann_indef_naan"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | kanishka/counterfactual_babylm_aann_indef_naan | [
"region:us"
] | 2023-12-11T22:28:37+00:00 | {"dataset_info": {"features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 581833803, "num_examples": 11632617}, {"name": "validation", "num_bytes": 56120230, "num_examples": 1026747}], "download_size": 0, "dataset_size": 637954033}} | 2023-12-13T01:24:56+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "counterfactual_babylm_aann_indef_naan"
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87633873af0ae9ce27877f0dd14da3c57af763be | # Dataset Card for "counterfactual_babylm_aann_all_det_naan"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | kanishka/counterfactual_babylm_aann_all_det_naan | [
"region:us"
] | 2023-12-11T22:28:58+00:00 | {"dataset_info": {"features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 581871758, "num_examples": 11632617}, {"name": "validation", "num_bytes": 56120230, "num_examples": 1026747}], "download_size": 0, "dataset_size": 637991988}} | 2023-12-13T01:24:57+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "counterfactual_babylm_aann_all_det_naan"
More Information needed | [
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11891b25af35971e56d5ef486b7c5f24b8c488b9 | # Dataset Card for "counterfactual_babylm_aann_indef_removal"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | kanishka/counterfactual_babylm_aann_indef_removal | [
"region:us"
] | 2023-12-11T22:29:21+00:00 | {"dataset_info": {"features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 581821948, "num_examples": 11635848}, {"name": "validation", "num_bytes": 56120230, "num_examples": 1026747}], "download_size": 0, "dataset_size": 637942178}} | 2023-12-13T01:24:58+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "counterfactual_babylm_aann_indef_removal"
More Information needed | [
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c6fcdfff8a027cceb05edc30010ceb8a6aa3b5bd | # Dataset Card for "counterfactual_babylm_aann_all_det_removal"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | kanishka/counterfactual_babylm_aann_all_det_removal | [
"region:us"
] | 2023-12-11T22:29:45+00:00 | {"dataset_info": {"features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 581806165, "num_examples": 11647204}, {"name": "validation", "num_bytes": 56120230, "num_examples": 1026747}], "download_size": 0, "dataset_size": 637926395}} | 2023-12-13T01:24:59+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "counterfactual_babylm_aann_all_det_removal"
More Information needed | [
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d62fa0059d2533349b9bcea55d236ed44b0e1c27 | # Dataset Card for "counterfactual_training_test"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | kanishka/counterfactual_training_test | [
"region:us"
] | 2023-12-11T22:30:04+00:00 | {"dataset_info": {"features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 79390, "num_examples": 1000}, {"name": "validation", "num_bytes": 56120230, "num_examples": 1026747}], "download_size": 0, "dataset_size": 56199620}} | 2023-12-13T01:25:00+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "counterfactual_training_test"
More Information needed | [
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df1985911592fd6c0b941617e798194734b5c661 | # Dataset Card for "counterfactual_babylm_aann_indef_articles_with_pl_nouns_removal"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | kanishka/counterfactual_babylm_aann_indef_articles_with_pl_nouns_removal | [
"region:us"
] | 2023-12-11T22:30:12+00:00 | {"dataset_info": {"features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 581810331, "num_examples": 11662188}, {"name": "validation", "num_bytes": 56120230, "num_examples": 1026747}], "download_size": 421777159, "dataset_size": 637930561}} | 2023-12-11T22:30:29+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "counterfactual_babylm_aann_indef_articles_with_pl_nouns_removal"
More Information needed | [
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7e6a211dbd0bf8a7c1bdfdfe767c0e6bdf2f1cdc | # Dataset Card for "librispeech_asr-audiodec_encodec_24k"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | anthony-wss/librispeech_asr-audiodec_encodec_24k | [
"region:us"
] | 2023-12-11T23:05:24+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "train.clean.360", "path": "data/train.clean.360-*"}, {"split": "train.other.500", "path": "data/train.other.500-*"}]}], "dataset_info": {"features": [{"name": "text", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "unit", "sequence": {"s... | 2023-12-12T00:25:07+00:00 | [] | [] | TAGS
#region-us
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More Information needed | [
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1997a636fefd497a2a942c373fa54ac5e61a6f9c | # Dataset Card for "metal-python-ood-climate-explanatations"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | lum-ai/metal-python-ood-climate-explanatations | [
"region:us"
] | 2023-12-11T23:22:05+00:00 | {"dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "chunk_id", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "start_text", "dtype": "int64"}, {"name": "stop_text", "dtype": "int64"}, {"name": "code", "dtype": "string"}, {"name": "start_code", "dtype": "int64"}, {"name": "stop... | 2023-12-11T23:22:07+00:00 | [] | [] | TAGS
#region-us
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More Information needed | [
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c27a4a09d45d6ab62ad684d1e6db482b52622f71 | # Dataset Card for "augmented-vsr-v2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | ktennyson6/augmented-vsr-v2 | [
"region:us"
] | 2023-12-11T23:58:46+00:00 | {"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "text", "dtype": "string"}, {"name": "relation", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 981790431.631, "num_examples": 6237}], "download_size": 852413763, "dataset_size": 981790431.631}} | 2023-12-11T23:59:31+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "augmented-vsr-v2"
More Information needed | [
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f149ba2f74a66c771992e74164139b4ea97349da | # Code de la sécurité sociale, non-instruct (11-12-2023)
This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusti... | louisbrulenaudet/code-securite-sociale | [
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This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusti... | [
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73a8e29a0fa9aa9c5be5939051156154ac1d0791 | # Code pénal, non-instruct (11-12-2023)
This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the model's pa... | louisbrulenaudet/code-penal | [
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This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the model's pa... | [
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cb88e175ef8e96e98fa920355beb60a3a9674983 | # Code du sport, non-instruct (11-12-2023)
This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the model's... | louisbrulenaudet/code-sport | [
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This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice.
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b26327c0043acd0a0b087a7e33f29747d8670827 | # Code civil, non-instruct (11-12-2023)
This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the model's pa... | louisbrulenaudet/code-civil | [
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This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice.
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523b291b9c268f606d9ccb08cda1adadc5a79916 | # Code de commerce, non-instruct (11-12-2023)
This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the mode... | louisbrulenaudet/code-commerce | [
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"... | 2023-12-12T01:47:31+00:00 | {"language": ["fr"], "license": "apache-2.0", "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-generation", "table-question-answering", "summarization", "conversational"], "pretty_name": "Code de commerce", "tags": ["finetuning", "legal", "f... | 2023-12-12T10:40:35+00:00 | [] | [
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This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the mode... | [
"# Code de commerce, non-instruct (11-12-2023)\n\nThis project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice. \n\nFine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting... | [
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700b5f5a8b63323878697e98013f3a5088afb518 | # Orca-DPO-Pairs-KO
Intel/orca_dpo_pais 를 한국어로 번역한 데이터세트 입니다.
번역은 maywell/Syntra-7B-v0.3-Translation 을 사용했습니다. 번역 후 일부 오류가 발생한 라인은 삭제했기 때문에 원본과 차이가 있을 수 있습니다. | Ja-ck/Orca-DPO-Pairs-KO | [
"size_categories:10K<n<100K",
"language:ko",
"license:apache-2.0",
"region:us"
] | 2023-12-12T01:56:54+00:00 | {"language": ["ko"], "license": "apache-2.0", "size_categories": ["10K<n<100K"]} | 2023-12-12T01:58:39+00:00 | [] | [
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#size_categories-10K<n<100K #language-Korean #license-apache-2.0 #region-us
| # Orca-DPO-Pairs-KO
Intel/orca_dpo_pais 를 한국어로 번역한 데이터세트 입니다.
번역은 maywell/Syntra-7B-v0.3-Translation 을 사용했습니다. 번역 후 일부 오류가 발생한 라인은 삭제했기 때문에 원본과 차이가 있을 수 있습니다. | [
"# Orca-DPO-Pairs-KO\n\nIntel/orca_dpo_pais 를 한국어로 번역한 데이터세트 입니다.\n\n번역은 maywell/Syntra-7B-v0.3-Translation 을 사용했습니다. 번역 후 일부 오류가 발생한 라인은 삭제했기 때문에 원본과 차이가 있을 수 있습니다."
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] |
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# More Information Needed
E-mail: tomoki.fujihara.p3@dc.tohoku.ac.jp | TomokiFujihara/japanese_offensiveness_estimation_dataset | [
"license:apache-2.0",
"region:us"
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#license-apache-2.0 #region-us
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# Dataset Card for Evaluation run of TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T](https://huggingface.co/TinyLlama/TinyLlama-1... | open-llm-leaderboard/details_TinyLlama__TinyLlama-1.1B-intermediate-step-1195k-token-2.5T | [
"region:us"
] | 2023-12-12T02:56:04+00:00 | {"pretty_name": "Evaluation run of TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T", "dataset_summary": "Dataset automatically created during the evaluation run of model [TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-toke... | 2023-12-12T02:56:44+00:00 | [] | [] | TAGS
#region-us
|
# Dataset Card for Evaluation run of TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T
Dataset automatically created during the evaluation run of model TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one corespondi... | [
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- original dataset: [korean data from kaist-ai/Multilingual-CoT-Collection](https://huggingface.co/datasets/kaist-ai/Multilingual-CoT-Collection) | heegyu/CoT-collection-ko | [
"license:cc-by-4.0",
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | Lask8/gradio-lipsync-wav2lip | [
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] | 2023-12-12T03:28:46+00:00 | {"license": "apache-2.0", "title": "Gradio Lipsync Wav2lip", "emoji": "\ud83d\udc44", "colorFrom": "indigo", "colorTo": "blue", "sdk": "gradio", "python_version": 3.8, "sdk_version": "3.40.1", "suggested_hardware": "t4-medium", "app_file": "app.py", "pinned": false} | 2023-12-12T03:50:04+00:00 | [] | [] | TAGS
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703a2a8741e862f4491cfd365eb402428d95262b |
# Dataset Card for Evaluation run of janhq/supermario-slerp
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [janhq/supermario-slerp](https://huggingface.co/janhq/supermario-slerp) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFace... | open-llm-leaderboard/details_janhq__supermario-slerp | [
"region:us"
] | 2023-12-12T03:40:07+00:00 | {"pretty_name": "Evaluation run of janhq/supermario-slerp", "dataset_summary": "Dataset automatically created during the evaluation run of model [janhq/supermario-slerp](https://huggingface.co/janhq/supermario-slerp) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\nThe... | 2023-12-12T03:40:50+00:00 | [] | [] | TAGS
#region-us
|
# Dataset Card for Evaluation run of janhq/supermario-slerp
Dataset automatically created during the evaluation run of model janhq/supermario-slerp on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(... | [
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# Dataset Card for Evaluation run of mistralai/Mistral-7B-Instruct-v0.2
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the [Open LLM Leaderboard](https... | open-llm-leaderboard/details_mistralai__Mistral-7B-Instruct-v0.2 | [
"region:us"
] | 2023-12-12T03:40:42+00:00 | {"pretty_name": "Evaluation run of mistralai/Mistral-7B-Instruct-v0.2", "dataset_summary": "Dataset automatically created during the evaluation run of model [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/Hugging... | 2023-12-12T03:41:32+00:00 | [] | [] | TAGS
#region-us
|
# Dataset Card for Evaluation run of mistralai/Mistral-7B-Instruct-v0.2
Dataset automatically created during the evaluation run of model mistralai/Mistral-7B-Instruct-v0.2 on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has ... | [
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# Dataset Card for Evaluation run of wang7776/Llama-2-7b-chat-hf-30-sparsity
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [wang7776/Llama-2-7b-chat-hf-30-sparsity](https://huggingface.co/wang7776/Llama-2-7b-chat-hf-30-sparsity) on the [Open LLM Lea... | open-llm-leaderboard/details_wang7776__Llama-2-7b-chat-hf-30-sparsity | [
"region:us"
] | 2023-12-12T03:40:53+00:00 | {"pretty_name": "Evaluation run of wang7776/Llama-2-7b-chat-hf-30-sparsity", "dataset_summary": "Dataset automatically created during the evaluation run of model [wang7776/Llama-2-7b-chat-hf-30-sparsity](https://huggingface.co/wang7776/Llama-2-7b-chat-hf-30-sparsity) on the [Open LLM Leaderboard](https://huggingface.co... | 2023-12-12T03:41:40+00:00 | [] | [] | TAGS
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# Dataset Card for Evaluation run of wang7776/Llama-2-7b-chat-hf-30-sparsity
Dataset automatically created during the evaluation run of model wang7776/Llama-2-7b-chat-hf-30-sparsity on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The da... | [
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19dcd7027a51f9db6893c1b630a89fcf199937b3 | a quick and light dataset designed to PEFT fine-tune mistral 7B and improve upon its reasoning skills
a fine-tuned and quantized model using this dataset can be found at netcat420/MHENN (successor coming soon) | netcat420/quiklogik | [
"license:mit",
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] | 2023-12-12T03:50:41+00:00 | {"license": "mit"} | 2023-12-20T03:19:37+00:00 | [] | [] | TAGS
#license-mit #region-us
| a quick and light dataset designed to PEFT fine-tune mistral 7B and improve upon its reasoning skills
a fine-tuned and quantized model using this dataset can be found at netcat420/MHENN (successor coming soon) | [] | [
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# Dataset Card for Evaluation run of rwitz2/pee
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [rwitz2/pee](https://huggingface.co/rwitz2/pee) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The datas... | open-llm-leaderboard/details_rwitz2__pee | [
"region:us"
] | 2023-12-12T03:54:29+00:00 | {"pretty_name": "Evaluation run of rwitz2/pee", "dataset_summary": "Dataset automatically created during the evaluation run of model [rwitz2/pee](https://huggingface.co/rwitz2/pee) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\nThe dataset is composed of 63 configura... | 2023-12-12T03:55:20+00:00 | [] | [] | TAGS
#region-us
|
# Dataset Card for Evaluation run of rwitz2/pee
Dataset automatically created during the evaluation run of model rwitz2/pee on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be foun... | [
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# Dataset Card for Evaluation run of janhq/supermario-v1
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [janhq/supermario-v1](https://huggingface.co/janhq/supermario-v1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_l... | open-llm-leaderboard/details_janhq__supermario-v1 | [
"region:us"
] | 2023-12-12T03:54:50+00:00 | {"pretty_name": "Evaluation run of janhq/supermario-v1", "dataset_summary": "Dataset automatically created during the evaluation run of model [janhq/supermario-v1](https://huggingface.co/janhq/supermario-v1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\nThe dataset ... | 2023-12-12T03:55:52+00:00 | [] | [] | TAGS
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# Dataset Card for Evaluation run of janhq/supermario-v1
Dataset automatically created during the evaluation run of model janhq/supermario-v1 on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Ea... | [
"# Dataset Card for Evaluation run of janhq/supermario-v1\n\n\n\nDataset automatically created during the evaluation run of model janhq/supermario-v1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from ... | [
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"# Dataset Card for Evaluation run of janhq/supermario-v1\n\n\n\nDataset automatically created during the evaluation run of model janhq/supermario-v1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe datas... | [
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"passage: TAGS\n#region-us \n# Dataset Card for Evaluation run of janhq/supermario-v1\n\n\n\nDataset automatically created during the evaluation run of model janhq/supermario-v1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe da... |
ba8456cbfe5eee81e078bd3a63611dc9aa1a539c |
# Dataset Card for Evaluation run of Fredithefish/MadMix-v0.1
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Fredithefish/MadMix-v0.1](https://huggingface.co/Fredithefish/MadMix-v0.1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/Huggi... | open-llm-leaderboard/details_Fredithefish__MadMix-v0.1 | [
"region:us"
] | 2023-12-12T03:55:48+00:00 | {"pretty_name": "Evaluation run of Fredithefish/MadMix-v0.1", "dataset_summary": "Dataset automatically created during the evaluation run of model [Fredithefish/MadMix-v0.1](https://huggingface.co/Fredithefish/MadMix-v0.1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\... | 2023-12-12T03:56:35+00:00 | [] | [] | TAGS
#region-us
|
# Dataset Card for Evaluation run of Fredithefish/MadMix-v0.1
Dataset automatically created during the evaluation run of model Fredithefish/MadMix-v0.1 on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 ... | [
"# Dataset Card for Evaluation run of Fredithefish/MadMix-v0.1\n\n\n\nDataset automatically created during the evaluation run of model Fredithefish/MadMix-v0.1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been cre... | [
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"# Dataset Card for Evaluation run of Fredithefish/MadMix-v0.1\n\n\n\nDataset automatically created during the evaluation run of model Fredithefish/MadMix-v0.1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\... | [
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"passage: TAGS\n#region-us \n# Dataset Card for Evaluation run of Fredithefish/MadMix-v0.1\n\n\n\nDataset automatically created during the evaluation run of model Fredithefish/MadMix-v0.1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.... |
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# Dataset Card for Evaluation run of rwitz2/ipo-test
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [rwitz2/ipo-test](https://huggingface.co/rwitz2/ipo-test) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboa... | open-llm-leaderboard/details_rwitz2__ipo-test | [
"region:us"
] | 2023-12-12T03:56:24+00:00 | {"pretty_name": "Evaluation run of rwitz2/ipo-test", "dataset_summary": "Dataset automatically created during the evaluation run of model [rwitz2/ipo-test](https://huggingface.co/rwitz2/ipo-test) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\nThe dataset is composed ... | 2023-12-12T03:57:07+00:00 | [] | [] | TAGS
#region-us
|
# Dataset Card for Evaluation run of rwitz2/ipo-test
Dataset automatically created during the evaluation run of model rwitz2/ipo-test on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run c... | [
"# Dataset Card for Evaluation run of rwitz2/ipo-test\n\n\n\nDataset automatically created during the evaluation run of model rwitz2/ipo-test on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s)... | [
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"# Dataset Card for Evaluation run of rwitz2/ipo-test\n\n\n\nDataset automatically created during the evaluation run of model rwitz2/ipo-test on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has b... | [
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"passage: TAGS\n#region-us \n# Dataset Card for Evaluation run of rwitz2/ipo-test\n\n\n\nDataset automatically created during the evaluation run of model rwitz2/ipo-test on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset ha... |
229ac5e9ee3a0832d9af349e514c73ec842f49c1 |
# Dataset Card for Evaluation run of Felladrin/TinyMistral-248M-SFT-v4
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Felladrin/TinyMistral-248M-SFT-v4](https://huggingface.co/Felladrin/TinyMistral-248M-SFT-v4) on the [Open LLM Leaderboard](https://... | open-llm-leaderboard/details_Felladrin__TinyMistral-248M-SFT-v4 | [
"region:us"
] | 2023-12-12T04:18:24+00:00 | {"pretty_name": "Evaluation run of Felladrin/TinyMistral-248M-SFT-v4", "dataset_summary": "Dataset automatically created during the evaluation run of model [Felladrin/TinyMistral-248M-SFT-v4](https://huggingface.co/Felladrin/TinyMistral-248M-SFT-v4) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFac... | 2023-12-12T04:19:10+00:00 | [] | [] | TAGS
#region-us
|
# Dataset Card for Evaluation run of Felladrin/TinyMistral-248M-SFT-v4
Dataset automatically created during the evaluation run of model Felladrin/TinyMistral-248M-SFT-v4 on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has be... | [
"# Dataset Card for Evaluation run of Felladrin/TinyMistral-248M-SFT-v4\n\n\n\nDataset automatically created during the evaluation run of model Felladrin/TinyMistral-248M-SFT-v4 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe da... | [
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"# Dataset Card for Evaluation run of Felladrin/TinyMistral-248M-SFT-v4\n\n\n\nDataset automatically created during the evaluation run of model Felladrin/TinyMistral-248M-SFT-v4 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the ... | [
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"passage: TAGS\n#region-us \n# Dataset Card for Evaluation run of Felladrin/TinyMistral-248M-SFT-v4\n\n\n\nDataset automatically created during the evaluation run of model Felladrin/TinyMistral-248M-SFT-v4 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of t... |
db9b9b2b82ce425d756ec9619aea06274f88b634 |
# Dataset Card for Evaluation run of Sao10K/NyakuraV2.1-m7
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Sao10K/NyakuraV2.1-m7](https://huggingface.co/Sao10K/NyakuraV2.1-m7) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/... | open-llm-leaderboard/details_Sao10K__NyakuraV2.1-m7 | [
"region:us"
] | 2023-12-12T04:33:49+00:00 | {"pretty_name": "Evaluation run of Sao10K/NyakuraV2.1-m7", "dataset_summary": "Dataset automatically created during the evaluation run of model [Sao10K/NyakuraV2.1-m7](https://huggingface.co/Sao10K/NyakuraV2.1-m7) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\nThe da... | 2023-12-12T04:34:32+00:00 | [] | [] | TAGS
#region-us
|
# Dataset Card for Evaluation run of Sao10K/NyakuraV2.1-m7
Dataset automatically created during the evaluation run of model Sao10K/NyakuraV2.1-m7 on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s)... | [
"# Dataset Card for Evaluation run of Sao10K/NyakuraV2.1-m7\n\n\n\nDataset automatically created during the evaluation run of model Sao10K/NyakuraV2.1-m7 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created f... | [
"TAGS\n#region-us \n",
"# Dataset Card for Evaluation run of Sao10K/NyakuraV2.1-m7\n\n\n\nDataset automatically created during the evaluation run of model Sao10K/NyakuraV2.1-m7 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe d... | [
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"passage: TAGS\n#region-us \n# Dataset Card for Evaluation run of Sao10K/NyakuraV2.1-m7\n\n\n\nDataset automatically created during the evaluation run of model Sao10K/NyakuraV2.1-m7 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nTh... |
39dee4fe420bcd43979189089a3c8eadceadfb56 |
# Dataset Card for Evaluation run of l3utterfly/minima-3b-layla-v1
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [l3utterfly/minima-3b-layla-v1](https://huggingface.co/l3utterfly/minima-3b-layla-v1) on the [Open LLM Leaderboard](https://huggingface.... | open-llm-leaderboard/details_l3utterfly__minima-3b-layla-v1 | [
"region:us"
] | 2023-12-12T05:25:37+00:00 | {"pretty_name": "Evaluation run of l3utterfly/minima-3b-layla-v1", "dataset_summary": "Dataset automatically created during the evaluation run of model [l3utterfly/minima-3b-layla-v1](https://huggingface.co/l3utterfly/minima-3b-layla-v1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm... | 2023-12-12T05:26:27+00:00 | [] | [] | TAGS
#region-us
|
# Dataset Card for Evaluation run of l3utterfly/minima-3b-layla-v1
Dataset automatically created during the evaluation run of model l3utterfly/minima-3b-layla-v1 on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been creat... | [
"# Dataset Card for Evaluation run of l3utterfly/minima-3b-layla-v1\n\n\n\nDataset automatically created during the evaluation run of model l3utterfly/minima-3b-layla-v1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset ha... | [
"TAGS\n#region-us \n",
"# Dataset Card for Evaluation run of l3utterfly/minima-3b-layla-v1\n\n\n\nDataset automatically created during the evaluation run of model l3utterfly/minima-3b-layla-v1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluate... | [
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"passage: TAGS\n#region-us \n# Dataset Card for Evaluation run of l3utterfly/minima-3b-layla-v1\n\n\n\nDataset automatically created during the evaluation run of model l3utterfly/minima-3b-layla-v1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evalu... |
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# Dataset Card for Evaluation run of janhq/supermario-v2
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [janhq/supermario-v2](https://huggingface.co/janhq/supermario-v2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_l... | open-llm-leaderboard/details_janhq__supermario-v2 | [
"region:us"
] | 2023-12-12T05:36:27+00:00 | {"pretty_name": "Evaluation run of janhq/supermario-v2", "dataset_summary": "Dataset automatically created during the evaluation run of model [janhq/supermario-v2](https://huggingface.co/janhq/supermario-v2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\nThe dataset ... | 2023-12-12T05:37:09+00:00 | [] | [] | TAGS
#region-us
|
# Dataset Card for Evaluation run of janhq/supermario-v2
Dataset automatically created during the evaluation run of model janhq/supermario-v2 on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Ea... | [
"# Dataset Card for Evaluation run of janhq/supermario-v2\n\n\n\nDataset automatically created during the evaluation run of model janhq/supermario-v2 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from ... | [
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"# Dataset Card for Evaluation run of janhq/supermario-v2\n\n\n\nDataset automatically created during the evaluation run of model janhq/supermario-v2 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe datas... | [
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"passage: TAGS\n#region-us \n# Dataset Card for Evaluation run of janhq/supermario-v2\n\n\n\nDataset automatically created during the evaluation run of model janhq/supermario-v2 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe da... |
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# Dataset Card for Evaluation run of Undi95/Clover3-17B
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Undi95/Clover3-17B](https://huggingface.co/Undi95/Clover3-17B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_... | open-llm-leaderboard/details_Undi95__Clover3-17B | [
"region:us"
] | 2023-12-12T06:13:20+00:00 | {"pretty_name": "Evaluation run of Undi95/Clover3-17B", "dataset_summary": "Dataset automatically created during the evaluation run of model [Undi95/Clover3-17B](https://huggingface.co/Undi95/Clover3-17B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\nThe dataset is ... | 2023-12-12T06:14:14+00:00 | [] | [] | TAGS
#region-us
|
# Dataset Card for Evaluation run of Undi95/Clover3-17B
Dataset automatically created during the evaluation run of model Undi95/Clover3-17B on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each... | [
"# Dataset Card for Evaluation run of Undi95/Clover3-17B\n\n\n\nDataset automatically created during the evaluation run of model Undi95/Clover3-17B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 ... | [
"TAGS\n#region-us \n",
"# Dataset Card for Evaluation run of Undi95/Clover3-17B\n\n\n\nDataset automatically created during the evaluation run of model Undi95/Clover3-17B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset... | [
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"passage: TAGS\n#region-us \n# Dataset Card for Evaluation run of Undi95/Clover3-17B\n\n\n\nDataset automatically created during the evaluation run of model Undi95/Clover3-17B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe data... |
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# Dataset Card for Evaluation run of Sao10K/Venomia-1.1-m7
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Sao10K/Venomia-1.1-m7](https://huggingface.co/Sao10K/Venomia-1.1-m7) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/... | open-llm-leaderboard/details_Sao10K__Venomia-1.1-m7 | [
"region:us"
] | 2023-12-12T06:22:45+00:00 | {"pretty_name": "Evaluation run of Sao10K/Venomia-1.1-m7", "dataset_summary": "Dataset automatically created during the evaluation run of model [Sao10K/Venomia-1.1-m7](https://huggingface.co/Sao10K/Venomia-1.1-m7) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\nThe da... | 2023-12-12T06:23:33+00:00 | [] | [] | TAGS
#region-us
|
# Dataset Card for Evaluation run of Sao10K/Venomia-1.1-m7
Dataset automatically created during the evaluation run of model Sao10K/Venomia-1.1-m7 on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s)... | [
"# Dataset Card for Evaluation run of Sao10K/Venomia-1.1-m7\n\n\n\nDataset automatically created during the evaluation run of model Sao10K/Venomia-1.1-m7 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created f... | [
"TAGS\n#region-us \n",
"# Dataset Card for Evaluation run of Sao10K/Venomia-1.1-m7\n\n\n\nDataset automatically created during the evaluation run of model Sao10K/Venomia-1.1-m7 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe d... | [
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"passage: TAGS\n#region-us \n# Dataset Card for Evaluation run of Sao10K/Venomia-1.1-m7\n\n\n\nDataset automatically created during the evaluation run of model Sao10K/Venomia-1.1-m7 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nTh... |
727781eada2f4a6bf2416aa676c0d8a80a018325 | A big shout out to AllenAI, you guys rock!
从[WildChat](https://huggingface.co/datasets/allenai/WildChat)中抽出中文对话,但是因为发现了很多重复对话，有的人会反复的用一个prompt进行提问，有的人会换3.5或4去问同样的问题，所以进行了简单的去重。
去重方法大致为，使用[bert-base-chinese](https://huggingface.co/bert-base-chinese)将第一个问题转换为embedding，使用[类knn的方法](https://arxiv.org/pdf/1708.00489.pdf)抽取... | lorinma/Slim-Wildchat-zh | [
"task_categories:conversational",
"task_categories:text-generation",
"size_categories:10K<n<100K",
"language:zh",
"arxiv:1708.00489",
"region:us"
] | 2023-12-12T06:26:19+00:00 | {"language": ["zh"], "size_categories": ["10K<n<100K"], "task_categories": ["conversational", "text-generation"]} | 2023-12-20T06:29:18+00:00 | [
"1708.00489"
] | [
"zh"
] | TAGS
#task_categories-conversational #task_categories-text-generation #size_categories-10K<n<100K #language-Chinese #arxiv-1708.00489 #region-us
| A big shout out to AllenAI, you guys rock!
从WildChat中抽出中文对话,但是因为发现了很多重复对话，有的人会反复的用一个prompt进行提问，有的人会换3.5或4去问同样的问题，所以进行了简单的去重。
去重方法大致为，使用bert-base-chinese将第一个问题转换为embedding，使用类knn的方法抽取了1万条。并转换成了sharegpt格式。
注意！在对话中发现了NSFW的内容，并没有进行过滤，使用请注意甄别。
你会找到三个jsonl文件：
* URL 是使用每一个单独的Dialogue的首个HumanQuestion为基础，采样的200个种子任务，用于Evol... | [] | [
"TAGS\n#task_categories-conversational #task_categories-text-generation #size_categories-10K<n<100K #language-Chinese #arxiv-1708.00489 #region-us \n"
] | [
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"passage: TAGS\n#task_categories-conversational #task_categories-text-generation #size_categories-10K<n<100K #language-Chinese #arxiv-1708.00489 #region-us \n"
] |
9673fd811dd8419c6c03a90ae1979e24631de853 | # Dataset Card for Financial Fraud Labeled Dataset
<!-- Provide a quick summary of the dataset. -->
## Dataset Details
This dataset collects financial filings from various companies submitted to the U.S. Securities and Exchange Commission (SEC). The dataset consists of 85 companies involved in fraudulent cases and a... | amitkedia/Financial-Fraud-Dataset | [
"task_categories:text-classification",
"size_categories:1K<n<10K",
"language:en",
"license:apache-2.0",
"finance",
"region:us"
] | 2023-12-12T06:31:55+00:00 | {"language": ["en"], "license": "apache-2.0", "size_categories": ["1K<n<10K"], "task_categories": ["text-classification"], "tags": ["finance"]} | 2023-12-19T14:17:46+00:00 | [] | [
"en"
] | TAGS
#task_categories-text-classification #size_categories-1K<n<10K #language-English #license-apache-2.0 #finance #region-us
| # Dataset Card for Financial Fraud Labeled Dataset
## Dataset Details
This dataset collects financial filings from various companies submitted to the U.S. Securities and Exchange Commission (SEC). The dataset consists of 85 companies involved in fraudulent cases and an equal number of companies not involved in frau... | [
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cbf63918eb06139b74f9bcc1b3c473fbb7321121 |
# Dataset Card for Evaluation run of AA051610/A12P
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [AA051610/A12P](https://huggingface.co/AA051610/A12P) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
... | open-llm-leaderboard/details_AA051610__A12P | [
"region:us"
] | 2023-12-12T07:00:27+00:00 | {"pretty_name": "Evaluation run of AA051610/A12P", "dataset_summary": "Dataset automatically created during the evaluation run of model [AA051610/A12P](https://huggingface.co/AA051610/A12P) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\nThe dataset is composed of 63 ... | 2023-12-12T07:01:10+00:00 | [] | [] | TAGS
#region-us
|
# Dataset Card for Evaluation run of AA051610/A12P
Dataset automatically created during the evaluation run of model AA051610/A12P on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can b... | [
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b68e196efae75f3f94b83ea110263b53d7edf89a | # Dataset Card for "gsm8k-processed"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | Tianduo/gsm8k-split | [
"region:us"
] | 2023-12-12T07:01:51+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}], "dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}, {"name": "ans", "dtype": "... | 2023-12-28T04:00:27+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "gsm8k-processed"
More Information needed | [
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9bb5dbb508df39d921c003fcf421f45f1a8886e9 | ## 小样本实体识别
收集实体识别的数据集, 将其整理成 prompt-response 的形式. 基于语言模型的实体识别.
该数据集可用于:
1. 指令语言模型训练.
2. 数据集创建. (特定领域有少量标注数据时, 可与此数据集一起训练模型, 然后生成样本用于数据标注).
在 prompt 生成过程中会加入一些 `示例`, 我们尽量使各实体的标签满足 `n_way, n_shot`.
### 样本示例
目前有三种实体标注的格式:
* (1)句子重写.
比如 `"今天天气怎样"` 改写为 `"<date>今天</date>天气怎么"`.
这种方式的好处是能够从结果推断出实体的具体位置.
* (2)... | qgyd2021/few_shot_ner_sft | [
"license:apache-2.0",
"arxiv:2004.01401",
"arxiv:2204.12061",
"region:us"
] | 2023-12-12T07:23:11+00:00 | {"license": "apache-2.0"} | 2023-12-27T02:25:23+00:00 | [
"2004.01401",
"2204.12061"
] | [] | TAGS
#license-apache-2.0 #arxiv-2004.01401 #arxiv-2204.12061 #region-us
| 小样本实体识别
-------
收集实体识别的数据集, 将其整理成 prompt-response 的形式. 基于语言模型的实体识别.
该数据集可用于:
1. 指令语言模型训练.
2. 数据集创建. (特定领域有少量标注数据时, 可与此数据集一起训练模型, 然后生成样本用于数据标注).
在 prompt 生成过程中会加入一些 '示例', 我们尽量使各实体的标签满足 'n\_way, n\_shot'.
### 样本示例
目前有三种实体标注的格式:
* (1)句子重写.
比如 '"今天天气怎样"' 改写为 '"今天天气怎么"'.
这种方式的好处是能够从结果推断出实体的具体位置.
* (2)jso... | [
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e77c177c687058e31a139cebba1fa868e9913b70 |
# Dataset Card for Evaluation run of janhq/supermario-slerp-v2
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [janhq/supermario-slerp-v2](https://huggingface.co/janhq/supermario-slerp-v2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/Hu... | open-llm-leaderboard/details_janhq__supermario-slerp-v2 | [
"region:us"
] | 2023-12-12T07:23:22+00:00 | {"pretty_name": "Evaluation run of janhq/supermario-slerp-v2", "dataset_summary": "Dataset automatically created during the evaluation run of model [janhq/supermario-slerp-v2](https://huggingface.co/janhq/supermario-slerp-v2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard... | 2023-12-12T07:24:03+00:00 | [] | [] | TAGS
#region-us
|
# Dataset Card for Evaluation run of janhq/supermario-slerp-v2
Dataset automatically created during the evaluation run of model janhq/supermario-slerp-v2 on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from ... | [
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91ccafb5229edc75c32d95624d2ca0f1dc6b7f99 | # Dataset Card for "Soldering-Data-pix2pix-1209-white-1"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | ouvic215/Soldering-Data-pix2pix-1209-white-1 | [
"region:us"
] | 2023-12-12T07:29:06+00:00 | {"dataset_info": {"features": [{"name": "mask_image", "dtype": "image"}, {"name": "text", "dtype": "string"}, {"name": "image", "dtype": "image"}], "splits": [{"name": "train", "num_bytes": 511555221.25, "num_examples": 6799}], "download_size": 510366317, "dataset_size": 511555221.25}} | 2023-12-12T07:34:34+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "Soldering-Data-pix2pix-1209-white-1"
More Information needed | [
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976186687f7a136f218b24dd80d0fbd3d65961f2 | converted https://huggingface.co/datasets/argilla/comparison-data-falcon-with-feedback?row=0 to more proper format | umarigan/falcon_feedback_instruction | [
"region:us"
] | 2023-12-12T07:29:35+00:00 | {"dataset_info": {"features": [{"name": "instruction", "dtype": "string"}, {"name": "chosen", "dtype": "string"}, {"name": "rejected", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 7942624, "num_examples": 7401}], "download_size": 5146500, "dataset_size": 7942624}, "configs": [{"config_name": "default"... | 2023-12-13T06:52:08+00:00 | [] | [] | TAGS
#region-us
| converted URL to more proper format | [] | [
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798d38e439aedb3961b9ade6e371eb311fabdab0 |
# Dataset Card for Evaluation run of xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M](https://huggingface.co/xzuyn/GPT-2-SlimO... | open-llm-leaderboard/details_xzuyn__GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M | [
"region:us"
] | 2023-12-12T07:36:01+00:00 | {"pretty_name": "Evaluation run of xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M", "dataset_summary": "Dataset automatically created during the evaluation run of model [xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M](https://huggingface.co/xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMat... | 2023-12-12T07:36:43+00:00 | [] | [] | TAGS
#region-us
|
# Dataset Card for Evaluation run of xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M
Dataset automatically created during the evaluation run of model xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresp... | [
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b20a3a95a05b0273fc49417e3afcfe599bd3e8f1 | # Dataset Card for "ParlaSpeech-HR"
Mirror of http://hdl.handle.net/11356/1494 .
The ParlaSpeech-HR dataset is built from parliamentary proceedings available in the Croatian part of the ParlaMint corpus and
the parliamentary recordings available from the Croatian Parliament's YouTube channel. The corpus consists of ... | 5roop/ParlaSpeech-HR | [
"region:us"
] | 2023-12-12T07:38:51+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "path": "data/test-*"}, {"split": "dev", "path": "data/dev-*"}]}], "dataset_info": {"features": [{"name": "audio", "dtype": "audio"}, {"name": "transcript", "dtype": "string"}, {"name": "norm_transcript"... | 2023-12-12T14:16:58+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "ParlaSpeech-HR"
Mirror of URL .
The ParlaSpeech-HR dataset is built from parliamentary proceedings available in the Croatian part of the ParlaMint corpus and
the parliamentary recordings available from the Croatian Parliament's YouTube channel. The corpus consists of segments 8-20 seconds
in len... | [
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a3a4f89b03173c106e01b1abbe546f8f8ab14437 | # Dataset Card for "Soldering-Data-pix2pix-1209-white-2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | ouvic215/Soldering-Data-pix2pix-1209-white-2 | [
"region:us"
] | 2023-12-12T07:40:53+00:00 | {"dataset_info": {"features": [{"name": "mask_image", "dtype": "image"}, {"name": "text", "dtype": "string"}, {"name": "image", "dtype": "image"}], "splits": [{"name": "train", "num_bytes": 2087059454.5, "num_examples": 25950}], "download_size": 1724200255, "dataset_size": 2087059454.5}} | 2023-12-12T07:44:45+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "Soldering-Data-pix2pix-1209-white-2"
More Information needed | [
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41a05ec50f517931deb208c2e9d1f7a476385ef9 | # The Effanie Dataset
This is the dataset for Effanie, the persuasive, confident, and helpful AI!
There are some helpful files for creating the dataset yourself. These include:
* [XLSM Conversion tool](./convertXLSM.py)
* [Parquet Conversion tool](./convertParquet.py)
* [The actua... | josiauhlol/effanie-AI | [
"task_categories:question-answering",
"task_categories:conversational",
"language:en",
"license:mit",
"effanie",
"chat",
"region:us"
] | 2023-12-12T08:01:00+00:00 | {"language": ["en"], "license": "mit", "task_categories": ["question-answering", "conversational"], "tags": ["effanie", "chat"]} | 2023-12-14T09:02:10+00:00 | [] | [
"en"
] | TAGS
#task_categories-question-answering #task_categories-conversational #language-English #license-mit #effanie #chat #region-us
| # The Effanie Dataset
!Logo
This is the dataset for Effanie, the persuasive, confident, and helpful AI!
There are some helpful files for creating the dataset yourself. These include:
* XLSM Conversion tool
* Parquet Conversion tool
* The actual XLSM
This is based off of the OpenOrca dataset. | [
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10c59b948f6d6a69a7568a78c7429a421734ab3d | # Vietnamese Legal Closed QA dataset
The dataset can be used for RAG Chatbot. It contains 160K samples where each sample in the dataset includes a question, K relevant contexts and an answer generated by OpenAI GPT-4.
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-c... | thanhdath/vietnamese_legal_closed_qa | [
"region:us"
] | 2023-12-12T08:21:47+00:00 | {"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "selected_contexts", "sequence": "string"}, {"name": "answer", "dtype": "string"}, {"name": "provider", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 974327420, "num_examples": 171278}], "download_size": 346818235, "datase... | 2023-12-20T09:57:59+00:00 | [] | [] | TAGS
#region-us
| # Vietnamese Legal Closed QA dataset
The dataset can be used for RAG Chatbot. It contains 160K samples where each sample in the dataset includes a question, K relevant contexts and an answer generated by OpenAI GPT-4.
More Information needed | [
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"passage: TAGS\n#region-us \n# Vietnamese Legal Closed QA dataset\n\nThe dataset can be used for RAG Chatbot. It contains 160K samples where each sample in the dataset includes a question, K relevant contexts and an answer generated by OpenAI GPT-4.\n\nMore Information needed"
] |
9cc086723aa21f2e61cf77dd0a37435e444b5595 | # Crawl Youtube
We crawled Malaysian and Singaporean youtube channels, total up to 60k audio files with total 185k hours.
URLs data at https://github.com/mesolitica/malaya-speech/tree/master/data/youtube/data
Notebooks at https://github.com/mesolitica/malaya-speech/tree/master/data/youtube
## How to load the data e... | malaysia-ai/crawl-youtube | [
"region:us"
] | 2023-12-12T08:24:27+00:00 | {"dataset_info": {"features": [{"name": "filename", "dtype": {"audio": {"sampling_rate": 16000}}}, {"name": "url", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 1068464089483.938, "num_examples": 59879}], "download_size": 16395869337, "dataset_size": 1068464089483.938}} | 2023-12-23T23:17:32+00:00 | [] | [] | TAGS
#region-us
| # Crawl Youtube
We crawled Malaysian and Singaporean youtube channels, total up to 60k audio files with total 185k hours.
URLs data at URL
Notebooks at URL
## How to load the data efficiently?
This is global hashing indices if the audio chunked with 30 seconds, read more at URL
## Licensing
| [
"# Crawl Youtube\n\nWe crawled Malaysian and Singaporean youtube channels, total up to 60k audio files with total 185k hours.\n\nURLs data at URL\n\nNotebooks at URL",
"## How to load the data efficiently?\n\n\n\n\n\nThis is global hashing indices if the audio chunked with 30 seconds, read more at URL",
"## Lic... | [
"TAGS\n#region-us \n",
"# Crawl Youtube\n\nWe crawled Malaysian and Singaporean youtube channels, total up to 60k audio files with total 185k hours.\n\nURLs data at URL\n\nNotebooks at URL",
"## How to load the data efficiently?\n\n\n\n\n\nThis is global hashing indices if the audio chunked with 30 seconds, rea... | [
6,
38,
29,
4
] | [
"passage: TAGS\n#region-us \n# Crawl Youtube\n\nWe crawled Malaysian and Singaporean youtube channels, total up to 60k audio files with total 185k hours.\n\nURLs data at URL\n\nNotebooks at URL## How to load the data efficiently?\n\n\n\n\n\nThis is global hashing indices if the audio chunked with 30 seconds, read m... |
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