id stringlengths 2 115 | author stringlengths 2 42 ⌀ | last_modified timestamp[us, tz=UTC] | downloads int64 0 8.87M | likes int64 0 3.84k | paperswithcode_id stringlengths 2 45 ⌀ | tags list | lastModified timestamp[us, tz=UTC] | createdAt stringlengths 24 24 | key stringclasses 1 value | created timestamp[us] | card stringlengths 1 1.01M | embedding list | library_name stringclasses 21 values | pipeline_tag stringclasses 27 values | mask_token null | card_data null | widget_data null | model_index null | config null | transformers_info null | spaces null | safetensors null | transformersInfo null | modelId stringlengths 5 111 ⌀ | embeddings list |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
hooool/tilled | hooool | 2023-10-31T18:20:20Z | 0 | 0 | null | [
"language:en",
"license:mit",
"region:us"
] | 2023-10-31T18:20:20Z | 2023-10-31T18:12:17.000Z | 2023-10-31T18:12:17 | ---
license: mit
language:
- en
pretty_name: tilled zendesk
--- | [
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zeio/auto-pale | zeio | 2023-10-31T21:25:58Z | 0 | 0 | null | [
"task_categories:text-generation",
"task_categories:text-classification",
"task_categories:automatic-speech-recognition",
"language_creators:crowdsourced",
"size_categories:10K<n<100K",
"language:en",
"license:apache-2.0",
"gaming",
"region:us"
] | 2023-10-31T21:25:58Z | 2023-10-31T19:18:21.000Z | 2023-10-31T19:18:21 | ---
language:
- en
license: apache-2.0
tags:
- gaming
annotation_creators:
- crowdsourced
language_creators:
- crowdsourced
pretty_name: pale
size_categories:
- 10K<n<100K
task_categories:
- text-generation
- text-classification
- automatic-speech-recognition
configs:
- config_name: quotes
data_files:
- split: train
path: quotes/*.parquet
default: true
- config_name: vanilla
data_files:
- split: train
path: vanilla/*.parquet
default: false
- config_name: annotated
data_files:
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path: annotated/*.parquet
default: false
- config_name: pulled
data_files:
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path: pulled/*.parquet
default: false
dataset_info:
- config_name: pulled
features:
- name: header
dtype: string
- name: subheader
dtype: string
- name: text
dtype: string
- name: sound
dtype:
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sampling_rate: 44100
- name: champion
dtype: string
splits:
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dataset_size: 4621864509.2
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---
# Dataset card for pale
## Table of contents
- [Dataset description](#dataset-description)
- [Dataset summary](#dataset-summary)
- [Dataset structure](#dataset-structure)
- [Dataset instance](#dataset-instance)
- [Dataset fields](#dataset-fields)
## Dataset description
- **Homepage:** [pale homepage](https://huggingface.co/datasets/zeio/pale)
- **Repository:** [pale repository](https://huggingface.co/datasets/zeio/pale)
- **Point of contact:** [Zeio Nara](mailto:zeionara@gmail.com)
- **Dataset version:** `30.10.2023`
### Dataset summary
This dataset contains league of legends champions' quotes parsed from [fandom](https://leagueoflegends.fandom.com).
See dataset usage example [at google colab](https://cutt.ly/3wEKDUI9).
The dataset is available in the following configurations:
1. `vanilla` - all data pulled from the website without significant modifications apart from the web page structure parsing;
1. `quotes` - truncated version of the corpus, which does't contain sound effects;
1. `annotated` - an extended version of the full configuration with a couple of additional columns with labels;
1. `pulled` - same as vanilla, but sound files have been pulled from the website, and `source` column is replaced with `sound`.
## Dataset structure
### Data instance
An example of an entry from the dataset is given below:
```json
{
"header": "Attack",
"subheader": "Attacking",
"text": "Kindred: \"The masks of the Kindred seek you!\"",
"source": "https://static.wikia.nocookie.net/leagueoflegends/images/1/12/Kindred_Original_Passive_Mark_Enemy_6.ogg/revision/latest?cb=20221204121356",
"champion": "kindred"
}
```
### Data fields
Each dataset entry therefore consists of the following fields:
- `header` - main category of the text;
- `subheader` - secondary category of the text (none in some cases);
- `text` - text said by the champion or description of sound made by the champion;
- `source` - link to the audio file (only `vanilla` configuration);
- `champion` - name of the champion in lowercase;
- `quote` - binary field displaying whether corresponding text contains quote or not (only `annotated` configuration);
- `sound` - audio data for the entry (only `pulled` configuration).
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joshuajewell/32000-BlackSharpie | joshuajewell | 2023-10-31T20:12:40Z | 0 | 0 | null | [
"task_categories:text-to-image",
"annotations_creators:human generated",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:n=33",
"language:en",
"license:cc0-1.0",
"region:us"
] | 2023-10-31T20:12:40Z | 2023-10-31T20:08:08.000Z | 2023-10-31T20:08:08 | ---
license: cc0-1.0
annotations_creators:
- human generated
language:
- en
language_creators:
- other
multilinguality:
- monolingual
pretty_name: Black Sharpie
size_categories:
- n=33
source_datasets:
tags: []
task_categories:
- text-to-image
task_ids: []
---
<h1>Dataset Card for a Black and White Sharpie Style</h1>
Dataset used to train/finetune a black and white sharpie style
Captions are generated by hand with the assistance of BLIP.
Images were hand drawn.
Text file filenames correspond image file filenames as captions. | [
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joshuajewell/FengZikai | joshuajewell | 2023-11-03T03:07:51Z | 0 | 0 | null | [
"task_categories:text-to-image",
"annotations_creators:human generated",
"language_creators:other",
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"license:unknown",
"region:us"
] | 2023-11-03T03:07:51Z | 2023-10-31T20:15:16.000Z | 2023-10-31T20:15:16 | ---
license: unknown
annotations_creators:
- human generated
language:
- en
language_creators:
- other
multilinguality:
- monolingual
pretty_name: Black Sharpie
size_categories:
- n=40
source_datasets: null
tags: []
task_categories:
- text-to-image
task_ids: []
---
<h1>Dataset Card for Feng Zikai</h1>
Dataset used to train/finetune in the art style of artist Feng Zikai
</br>Captions are generated by hand with the assistance of BLIP.
Images sourced from: http://www.chinaonlinemuseum.com/gallery-feng-zikai.php
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LuiMito/gostosa | LuiMito | 2023-10-31T20:53:17Z | 0 | 0 | null | [
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MAKHLWF/Myfiles | MAKHLWF | 2023-10-31T21:30:14Z | 0 | 0 | null | [
"region:us"
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xdmizo/q | xdmizo | 2023-10-31T21:56:20Z | 0 | 0 | null | [
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LuiMito/clipe | LuiMito | 2023-10-31T21:58:00Z | 0 | 0 | null | [
"region:us"
] | 2023-10-31T21:58:00Z | 2023-10-31T21:57:12.000Z | 2023-10-31T21:57:12 | Entry not found | [
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LuiMito/lani | LuiMito | 2023-10-31T23:00:04Z | 0 | 0 | null | [
"region:us"
] | 2023-10-31T23:00:04Z | 2023-10-31T22:59:45.000Z | 2023-10-31T22:59:45 | Entry not found | [
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sordonia/t0-1.6M | sordonia | 2023-10-31T23:21:55Z | 0 | 0 | null | [
"region:us"
] | 2023-10-31T23:21:55Z | 2023-10-31T23:20:04.000Z | 2023-10-31T23:20:04 | ---
configs:
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---
# Dataset Card for "t0-1.6M"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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cp500/synthetic_hebrew_medical_text | cp500 | 2023-11-02T00:05:12Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T00:05:12Z | 2023-11-01T00:01:59.000Z | 2023-11-01T00:01:59 | ---
dataset_info:
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configs:
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data_files:
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path: data/train-*
---
# Dataset Card for "synthetic_hebrew_medical_text"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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NoobPROBR/Felipe | NoobPROBR | 2023-11-01T01:03:08Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-01T01:03:08Z | 2023-11-01T01:00:00.000Z | 2023-11-01T01:00:00 | ---
license: openrail
---
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JoaoJunior/formatted-java-preprocessed-code-APR | JoaoJunior | 2023-11-01T01:30:51Z | 0 | 0 | null | [
"region:us"
] | 2023-11-01T01:30:51Z | 2023-11-01T01:29:50.000Z | 2023-11-01T01:29:50 | ---
dataset_info:
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configs:
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data_files:
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path: data/train-*
---
# Dataset Card for "formatted-java-preprocessed-code-APR"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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WangResearchLab/AgentInstruct | WangResearchLab | 2023-11-02T23:42:21Z | 0 | 0 | null | [
"size_categories:n<1K",
"language:en",
"arxiv:2310.03710",
"region:us"
] | 2023-11-02T23:42:21Z | 2023-11-01T02:05:55.000Z | 2023-11-01T02:05:55 | ---
configs:
- config_name: default
data_files:
- split: agentinstruct_instruction
path: instructions.parquet
language:
- en
size_categories:
- n<1K
---
# AgentInstruct: Agent Instructs Large Language Models to be General Zero-Shot Reasoners
The repo for paper [Agent Instructs Large Language Models to be General Zero-Shot Reasoners](https://arxiv.org/abs/2310.03710).
<p align="center">
📃 <a href="https://arxiv.org/abs/2310.03710" target="_blank">[Paper]</a> • 💻 <a href="https://github.com/wang-research-lab/agentinstruct" target="_blank">[Github]</a> • 🤗 <a href="https://huggingface.co/datasets/WangResearchLab/AgentInstruct" target="_blank">[HuggingFace]</a> • 📌 <a href="https://nlp.wustl.edu/blog/2023-11-02-agentinstruct/" target="_blank">[Blog]</a> • 📽 <a href="http://cgraywang.github.io/files/2023-agentinstruct-slides(10min).pdf" target="_blank">[Slides]</a> • 📋 <a href="http://cgraywang.github.io/files/2023-agentinstruct-poster.pdf" target="_blank">[Poster]</a>
</p>
## AgentInstruct Instruction Dataset
The **AgentInstruct** Instruction dataset contains agent instructions for the 29 datasets used in the paper. We encourage you to use our AgentInstruct methodology detailed in the paper and code to produce more instructions and evaluate on more datasets.
We provide an example of using the instructions and producing more instructions with our AgentInstruct below. The AgentInstruct Instruction dataset we used in the code is [here](https://huggingface.co/datasets/WangResearchLab/AgentInstruct/blob/main/instructions.json).
## Installation
Begin by cloning this repository:
```
git clone --recurse-submodules https://github.com/wang-research-lab/agentinstruct.git
```
Then, run the following to implement zero-shot AgentInstruct into the HELM submodule:
```
cd agentinstruct
bash src/agentinstruct/reasoning/helm_updates/update_helm.sh
```
Now, add the following api keys to `prod_env/credentials.conf`: `openaiApiKey` (from [here](https://openai.com/blog/openai-api)) and `bingSubscriptionKey` (from [here](https://www.microsoft.com/en-us/bing/apis/bing-web-search-api)). Use the following format:
```
openaiApiKey: [your key here]
bingSubscriptionKey: [your key here]
```
We would recommend using a [Python 3.10 docker image](https://hub.docker.com/layers/library/python/3.10/images/sha256-6eff601177b9fdfb85f383089b97468910ff59be129019b1588dc3f9ac862204?context=explore).
```
docker network create mynetwork
docker pull python:3.10
docker run --network=mynetwork -v ~/agentinstruct:/code/agentinstruct -it python:3.10 bash
```
Next, create a virtual enviroment:
```
cd /code/agentinstruct
python3 -m pip install virtualenv
python3 -m virtualenv -p python3.10 helm-venv
source helm-venv/bin/activate
```
Run the following to download the necessary dependencies:
```
pip install -e src/agentinstruct/reasoning/helm
pip install -r requirements.txt
```
*Note*: For running other models (vicuna-13b, llama-2-7b-chat, llama-2-13b-chat, llama-2-70b-chat), you must also follow the instructions [here](src/agentinstruct/reasoning/serve/README.md).
## Replicating Main Results
To replicate the main results on 28 datasets (excludes NewsQA for its license restrictions, see [here](src/agentinstruct/reasoning/helm_updates/src/helm/benchmark/scenarios/newsqa_scenario.py)) with a specific model (gpt-3.5-turbo, llama-2-7b-chat, llama-2-13b-chat, llama-2-70b-chat, vicuna-13b), run:
```
bash scripts/gpt-3.5-turbo.sh
bash scripts/llama-2-7b-chat.sh
bash scripts/llama-2-13b-chat.sh
bash scripts/llama-2-70b-chat.sh
bash scripts/vicuna-13b.sh
```
Results will be stored in ```benchmark_outputs/runs/{model}-agentinstruct/results.csv```.
## Customizing your Run
There are three key components of the zero-shot AgentInstruct pipeline: (1) generating agent instructions, (2) running reasoning steps with the instructions, and (3) formatting the results. In this section, we will look at each component in detail, focusing on a single dataset: AddSub. Note that nothing here is specific to AddSub, and can be applied to any dataset, or even a combination of datasets!
### Generating Agent Instructions
First, to generate the agent instructions for AddSub, run the following:
```
bash scripts/generate_agent_instructions.sh scripts/run_specs/simple-gpt-3.5-turbo.conf addsub
```
We'll create a configuration file that specifies the run configuration. As an example, we'll look at the configuration file ```scripts/run_specs/simple-gpt-3.5-turbo.conf```, which specifies the configuration of running the AddSub dataset using GPT-3.5 Turbo:
```
entries: [
{description: "addsub:model=openai/gpt-3.5-turbo-0301,max_train_instances=0,instructions=agentinstruct", priority: 1}
]
```
The agent instructions for the AddSub dataset will be saved in ```instructions/addsub/instructions.json```. The agent's input, as well as the web sources used and intermediate prompts, will be saved under ```instructions/addsub/inputs.json``` and ```instructions/addsub/metadata.json``` respectively.
### Running Reasoning Steps
We'll use the same configuration file as above. To run reasoning steps with zero-shot AgentInstruct on AddSub, run the following:
```
bash scripts/run_reasoning.sh scripts/run_specs/simple-gpt-3.5-turbo.conf addsub 1000
```
The first two parameters are identical to those above, and the third represents the number of instances to run reasoning steps on. The results will be stored in ```benchmark_outputs/runs/addsub```.
*Note*: By default, zero-shot AgentInstruct reasoning will be done using the latest set of instructions generated. To run reasoning with the instructions used in the paper, run this script before the run_reasoning command:
```
python scripts/replicate.py
```
### Format Results
To easily format the evaluation results, run:
```
python src/agentinstruct/eval/format_results.py --suite addsub
```
The evaluation results will be saved in ```benchmark_output/runs/addsub/results.csv```. To see the full text output by instance, open ```benchmark_output/runs/addsub/'addsub:model=openai_gpt-3.5-turbo-0301,max_train_instances=0,instructions=agentinstruct'/scenario_state.json``` and search for ```full_text```.
*Note*: Normally, the results are formatted after all the run spec descriptions in the configuration file have been run. To see for a single run spec description, view:
```
benchmark_output/runs/addsub/'addsub:model=openai_gpt-3.5-turbo-0301,max_train_instances=0,instructions=agentinstruct'/stats.json
```
### All Together Now
To run the above entire AgentInstruct pipeline in one go, run:
```
bash scripts/run.sh scripts/run_specs/simple-gpt-3.5-turbo.conf addsub 1000
```
This will run all 3 steps outlined above, and store the result in ```benchmark_outputs/runs/addsub```.
## Arguments
In this section, we'll cover various important run arguments.
### Run Configuration Arguments
A run spec describes a specific dataset to run. For example, the run spec for AddSub used above is:
```
{description: "addsub:model=openai/gpt-3.5-turbo-0301,max_train_instances=0,instructions=agentinstruct", priority: 1}
```
| argument | description | options|
|----|----|----|
| `model` | Model to use for inference. | `local/vicuna-13b` <br> `local/llama-2-7b-chat` <br> `local/llama-2-13b-chat` <br> `local/llama-2-70b-chat` <br> `openai/gpt-3.5-turbo-0301` |
| `max_train_instances` | Number of few shot examples to prepend. Few Shot is not recommended. | int |
| `instructions` | Optional prompting method to use. `None` corresponds to standard zeroshot. | `agentinstruct` <br> `zeroshotcot` <br> `None` |
*Note*: Several datasets have additional argument to specify the specific subset or task.
### Generating Agent Instructions Arguments
The main script to generate agent instructions is ```scripts/generate_agent_instructions.sh```. It takes the following 2 positional arguments:
| argument | description | options|
|----|----|----|
| 1st | Path to run spec file. | str |
| 2nd | Suite name under which to save instructions. | str |
Internally, the agent instructions are generated by first running dataset preprocessing (in ```src/agentinstruct/agent/utils/dataset_preprocessing.py```) and then running the instruction generation (in ```src/agentinstruct/agent/agent_instr_generation.py```). These are combined in ```src/agentinstruct/agent/agent_pipeline.py``` and called by ```scripts/generate_agent_instructions.sh```. GPT-4 is used as the agent LLM as in our paper.
### Running Reasoning Arguments
The main script to run reasoning is ```scripts/run_reasoning.sh```, which internally calls `helm-run`. It takes the following 4 positional arguments, as well as a placeholder for any additional argument to pass to `helm-run`:
| argument | description | options|
|----|--------------------------------------------------------------------------------------|----|
| 1st | Path to run spec file. | str |
| 2nd | Suite name under which to save outputs. | str |
| 3rd | Maximum number of instances to run. | int |
| 4th | Maximum number of threads from which to send requests. Defaults to 8 for all models. | int |
| 5th | Place holder for any additional argument to pass to `helm-run`. | str |
### Outputting Results Arguments
The main script to format the results is ```src/agentinstruct/eval/format_results.py```. It takes a single named argument:
| argument | description | options|
|----|----|----|
| --suite | Suite name under which to find outputs. | str |
## Replicating Additional Results
To replicate the zero-shot (`zeroshot`) and zero-shot CoT (`zeroshot`) modes, run:
```
bash scripts/run_reasoning.sh scripts/run_specs/{mode}/{model}-{mode}.conf {model}-{mode} 1000 8
python src/agentinstruct/eval/format_results.py --suite {model}-{mode}
```
where `{mode}` is `zeroshot` or `zeroshotcot` and `{model}` is `vicuna-13b`, `llama-2-7b-chat`, `llama-2-13b-chat`, `llama-2-70b-chat`, or `gpt-3.5-turbo`.
*Note*: For standard zero-shot runs, pass `skip-expander` as the 5th positional argument.
## Citation
```bibtex
@article{crispino2023agent,
title={Agent Instructs Large Language Models to be General Zero-Shot Reasoners},
author={Crispino, Nicholas and Montgomery, Kyle and Zeng, Fankun and Song, Dawn and Wang, Chenguang},
journal={arXiv preprint arXiv:2310.03710},
year={2023}
}
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# Dataset Card for "water_effects_prompts"
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# Dataset Card for "succulents_prompts"
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# Dataset Card for "app_mockup_prompts"
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# Dataset Card for "ghibli_stills_prompts"
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---
# Dataset Card for "qrecc_conversational_embeddings"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
health360/Ultrachat-Filtered-Multiple-Conversations-Alpaca-Style | health360 | 2023-11-01T07:41:41Z | 0 | 0 | null | [
"region:us"
] | 2023-11-01T07:41:41Z | 2023-11-01T07:37:43.000Z | 2023-11-01T07:37:43 | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 1201812388
num_examples: 207865
download_size: 0
dataset_size: 1201812388
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "Ultrachat-Filtered-Multiple-Conversations-Alpaca-Style"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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AA12312424/andylo-v10-20-1024-sdxl-tagger | AA12312424 | 2023-11-01T07:57:10Z | 0 | 0 | null | [
"region:us"
] | 2023-11-01T07:57:10Z | 2023-11-01T07:56:36.000Z | 2023-11-01T07:56:36 | Entry not found | [
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alfredplpl/genai-terminology-en-ja | alfredplpl | 2023-11-01T08:05:56Z | 0 | 0 | null | [
"size_categories:n<1K",
"language:en",
"language:ja",
"license:apache-2.0",
"region:us"
] | 2023-11-01T08:05:56Z | 2023-11-01T08:01:31.000Z | 2023-11-01T08:01:31 | ---
license: apache-2.0
language:
- en
- ja
size_categories:
- n<1K
---
生成AIの日英専門用語集です。正確さは保証しませんが、GPT-4などの頭に入れておくと綺麗に訳せると思います。 | [
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danielz01/forest-damage | danielz01 | 2023-11-01T08:37:53Z | 0 | 0 | null | [
"region:us"
] | 2023-11-01T08:37:53Z | 2023-11-01T08:12:13.000Z | 2023-11-01T08:12:13 | ---
dataset_info:
features:
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sequence: string
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splits:
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num_examples: 1537
download_size: 3539168325
dataset_size: 3527542816.427
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "forest-damage"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Kelvinloh/lady | Kelvinloh | 2023-11-01T09:18:00Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | 2023-11-01T09:18:00Z | 2023-11-01T09:17:05.000Z | 2023-11-01T09:17:05 | ---
license: mit
---
| [
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kit-nlp/Vulgar_Lexicon_of_Chittagonian_Dialect_of_Bangla_or_Bengali | kit-nlp | 2023-11-01T11:12:50Z | 0 | 1 | null | [
"task_categories:text-classification",
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"region:us"
] | 2023-11-01T11:12:50Z | 2023-11-01T10:54:54.000Z | 2023-11-01T10:54:54 | ---
license: apache-2.0
task_categories:
- text-classification
language:
- bn
size_categories:
- 1K<n<10K
---
A list of Chittagonian Dialect of Bangla vulgar words
If you use Vulgar Lexicon dataset, please cite the following paper:
```
@Article{app132111875,
AUTHOR = {Mahmud, Tanjim and Ptaszynski, Michal and Masui, Fumito},
TITLE = {Automatic Vulgar Word Extraction Method with Application to Vulgar Remark Detection in Chittagonian Dialect of Bangla},
JOURNAL = {Applied Sciences},
VOLUME = {13},
YEAR = {2023},
NUMBER = {21},
ARTICLE-NUMBER = {11875},
URL = {https://www.mdpi.com/2076-3417/13/21/11875},
ISSN = {2076-3417},
DOI = {10.3390/app132111875}
}
``` | [
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TanjimKIT/Vulgar_Lexicon_of_Chittagonian_Dialect_of_Bangla_or_Bengali | TanjimKIT | 2023-11-01T11:15:31Z | 0 | 0 | null | [
"task_categories:text-classification",
"size_categories:1K<n<10K",
"language:bn",
"license:apache-2.0",
"doi:10.57967/hf/1297",
"region:us"
] | 2023-11-01T11:15:31Z | 2023-11-01T11:08:04.000Z | 2023-11-01T11:08:04 | ---
license: apache-2.0
task_categories:
- text-classification
language:
- bn
size_categories:
- 1K<n<10K
---
A list of Chittagonian Dialect of Bangla vulgar words
If you use Vulgar Lexicon dataset, please cite the following paper:
```
@Article{app132111875,
AUTHOR = {Mahmud, Tanjim and Ptaszynski, Michal and Masui, Fumito},
TITLE = {Automatic Vulgar Word Extraction Method with Application to Vulgar Remark Detection in Chittagonian Dialect of Bangla},
JOURNAL = {Applied Sciences},
VOLUME = {13},
YEAR = {2023},
NUMBER = {21},
ARTICLE-NUMBER = {11875},
URL = {https://www.mdpi.com/2076-3417/13/21/11875},
ISSN = {2076-3417},
DOI = {10.3390/app132111875}
}
``` | [
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0.413207918405... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
kdawoud91/news_articles_NLP801 | kdawoud91 | 2023-11-01T13:02:14Z | 0 | 0 | null | [
"region:us"
] | 2023-11-01T13:02:14Z | 2023-11-01T13:01:15.000Z | 2023-11-01T13:01:15 | Entry not found | [
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RaulSalinasHerr/chilean_touristic_data | RaulSalinasHerr | 2023-11-01T21:40:05Z | 0 | 0 | null | [
"task_categories:time-series-forecasting",
"size_categories:100K<n<1M",
"language:es",
"license:apache-2.0",
"region:us"
] | 2023-11-01T21:40:05Z | 2023-11-01T14:44:32.000Z | 2023-11-01T14:44:32 | ---
license: apache-2.0
task_categories:
- time-series-forecasting
language:
- es
size_categories:
- 100K<n<1M
--- | [
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-0.0478260256350... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
Sheokedech/id-ibnt | Sheokedech | 2023-11-01T15:14:52Z | 0 | 0 | null | [
"region:us"
] | 2023-11-01T15:14:52Z | 2023-11-01T14:57:09.000Z | 2023-11-01T14:57:09 | ---
configs:
- config_name: default
data_files:
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path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
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dtype: audio
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splits:
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num_examples: 4222
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num_bytes: 856481987.936
num_examples: 1512
download_size: 1900578091
dataset_size: 3065944850.546
---
# Dataset Card for "id-ibnt"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Mira-LeafTown/sd-configs | Mira-LeafTown | 2023-11-28T11:02:02Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T11:02:02Z | 2023-11-01T15:24:25.000Z | 2023-11-01T15:24:25 | Entry not found | [
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ClaireOzzz/collageTest | ClaireOzzz | 2023-11-01T16:18:30Z | 0 | 0 | null | [
"region:us"
] | 2023-11-01T16:18:30Z | 2023-11-01T16:18:27.000Z | 2023-11-01T16:18:27 | Entry not found | [
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... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
ClaireOzzz/collage | ClaireOzzz | 2023-11-01T16:20:01Z | 0 | 0 | null | [
"region:us"
] | 2023-11-01T16:20:01Z | 2023-11-01T16:19:59.000Z | 2023-11-01T16:19:59 | Entry not found | [
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... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
iashchak/igor_link_dialogues_rendered | iashchak | 2023-11-01T16:36:59Z | 0 | 0 | null | [
"region:us"
] | 2023-11-01T16:36:59Z | 2023-11-01T16:33:33.000Z | 2023-11-01T16:33:33 | ---
dataset_info:
features:
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dtype: string
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struct:
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splits:
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num_bytes: 29950800
num_examples: 31516
download_size: 15605747
dataset_size: 29950800
configs:
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data_files:
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path: data/train-*
---
# Dataset Card for "igor_link_dialogues_rendered"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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tsuyuan/gptspeech_amazon_google_tencent | tsuyuan | 2023-11-01T19:03:16Z | 0 | 0 | null | [
"region:us"
] | 2023-11-01T19:03:16Z | 2023-11-01T17:11:27.000Z | 2023-11-01T17:11:27 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: eval
path: data/eval-*
dataset_info:
features:
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sequence: int32
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sequence: int8
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sequence:
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splits:
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num_bytes: 13396628973
num_examples: 169967
download_size: 16698860181
dataset_size: 539549631894
---
# Dataset Card for "gptspeech_amazon_google_tencent"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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osbm/semi-private-dataset | osbm | 2023-11-01T17:30:25Z | 0 | 0 | null | [
"region:us"
] | 2023-11-01T17:30:25Z | 2023-11-01T17:30:25.000Z | 2023-11-01T17:30:25 | Entry not found | [
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patrickvonplaten/some_audios | patrickvonplaten | 2023-11-01T18:29:54Z | 0 | 0 | null | [
"region:us"
] | 2023-11-01T18:29:54Z | 2023-11-01T18:29:36.000Z | 2023-11-01T18:29:36 | Entry not found | [
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... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
Fraternitas/ElektraGoFAQs-en | Fraternitas | 2023-11-01T22:49:33Z | 0 | 0 | null | [
"task_categories:question-answering",
"size_categories:n<1K",
"language:en",
"finance",
"region:us"
] | 2023-11-01T22:49:33Z | 2023-11-01T18:30:13.000Z | 2023-11-01T18:30:13 | ---
task_categories:
- question-answering
language:
- en
tags:
- finance
pretty_name: tiny_FAQs
size_categories:
- n<1K
---
This is the dataset used to fine tuning (train) the LLama2.
This dataset has the original questios (FAQs), with only 37 samples and 2 features (questions and answers).
This version dataset is in ENLIGSH:
Another dataset was created to increase the number of samples by applying data augmentation (synthetic data). Check dataset in Fraternitas repo | [
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0.292351812124... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
nekofura/zero_one | nekofura | 2023-11-01T18:52:04Z | 0 | 0 | null | [
"task_categories:text-generation",
"license:apache-2.0",
"kamen_rider",
"zero-one",
"region:us"
] | 2023-11-01T18:52:04Z | 2023-11-01T18:40:15.000Z | 2023-11-01T18:40:15 | ---
license: apache-2.0
task_categories:
- text-generation
tags:
- kamen_rider
- zero-one
--- | [
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HamdanXI/lj-inprogress | HamdanXI | 2023-11-01T18:49:16Z | 0 | 0 | null | [
"region:us"
] | 2023-11-01T18:49:16Z | 2023-11-01T18:45:37.000Z | 2023-11-01T18:45:37 | ---
configs:
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download_size: 3784764912
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---
# Dataset Card for "lj-inprogress"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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kaitchup/opus-Norwegian-to-English | kaitchup | 2023-11-01T19:15:06Z | 0 | 0 | null | [
"region:us"
] | 2023-11-01T19:15:06Z | 2023-11-01T19:15:00.000Z | 2023-11-01T19:15:00 | ---
configs:
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dataset_info:
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---
# Dataset Card for "opus-no-en"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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kaitchup/opus-Vietnamese-to-English | kaitchup | 2023-11-01T19:15:12Z | 0 | 0 | null | [
"region:us"
] | 2023-11-01T19:15:12Z | 2023-11-01T19:15:06.000Z | 2023-11-01T19:15:06 | ---
configs:
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dataset_info:
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---
# Dataset Card for "opus-vi-en"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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kaitchup/opus-Dutch-to-English | kaitchup | 2023-11-01T19:15:29Z | 0 | 1 | null | [
"region:us"
] | 2023-11-01T19:15:29Z | 2023-11-01T19:15:23.000Z | 2023-11-01T19:15:23 | ---
configs:
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---
# Dataset Card for "opus-nl-en"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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kaitchup/opus-Danish-to-English | kaitchup | 2023-11-01T19:15:35Z | 0 | 0 | null | [
"region:us"
] | 2023-11-01T19:15:35Z | 2023-11-01T19:15:30.000Z | 2023-11-01T19:15:30 | ---
configs:
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dataset_info:
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---
# Dataset Card for "opus-da-en"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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TurcoLoko/modelorr | TurcoLoko | 2023-11-02T20:34:23Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | 2023-11-02T20:34:23Z | 2023-11-01T19:37:28.000Z | 2023-11-01T19:37:28 | ---
license: apache-2.0
---
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HuggingSara/med_mix | HuggingSara | 2023-11-01T21:09:42Z | 0 | 0 | null | [
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configs:
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---
# Dataset Card for "med_mix"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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newsmediabias/media-bias-data | newsmediabias | 2023-11-01T23:54:52Z | 0 | 0 | null | [
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newsmediabias/unlabeled_news_data | newsmediabias | 2023-11-02T00:01:15Z | 0 | 0 | null | [
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RogelioRobles/Chora | RogelioRobles | 2023-11-02T01:56:55Z | 0 | 0 | null | [
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license: unlicense
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herikhug/vozfernando | herikhug | 2023-11-02T03:11:42Z | 0 | 0 | null | [
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herikhug/vozferanandoum | herikhug | 2023-11-02T03:32:44Z | 0 | 0 | null | [
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herikhug/vozdofernando | herikhug | 2023-11-02T03:39:32Z | 0 | 0 | null | [
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DmitrMakeev/test_set | DmitrMakeev | 2023-11-02T04:01:23Z | 0 | 0 | null | [
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license: openrail
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ClaireOzzz/Collage_test3 | ClaireOzzz | 2023-11-02T04:28:24Z | 0 | 0 | null | [
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Deojoandco/capstone_fromgpt_without_gold_all | Deojoandco | 2023-11-02T04:34:50Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T04:34:50Z | 2023-11-02T04:34:47.000Z | 2023-11-02T04:34:47 | ---
dataset_info:
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splits:
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configs:
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---
# Dataset Card for "capstone_fromgpt_without_gold"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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DamarJati/Example-YOLO | DamarJati | 2023-11-02T07:02:08Z | 0 | 0 | null | [
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cs330/data-addmult-231019 | cs330 | 2023-11-02T06:04:11Z | 0 | 0 | null | [
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cellophaneZR/AE_dataset | cellophaneZR | 2023-11-02T07:20:24Z | 0 | 0 | null | [
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"region:us"
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license: cc-by-nc-4.0
---
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legacy107/newsqa-chunked-100 | legacy107 | 2023-11-02T07:33:03Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T07:33:03Z | 2023-11-02T07:32:54.000Z | 2023-11-02T07:32:54 | ---
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---
# Dataset Card for "newsqa-chunked-100"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Harvinder6766/sentiment_data_google | Harvinder6766 | 2023-11-02T07:52:46Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T07:52:46Z | 2023-11-02T07:51:03.000Z | 2023-11-02T07:51:03 | ---
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---
# Dataset Card for "sentiment_data_google"
Dataset for sentiment analysis on sentence level
Here we used google API to get doc level and sentiment level Score
* id2label = {0: "NEGATIVE", 1: "POSITIVE",2:"NEUTRAL"}
* label2id = {"NEGATIVE": 0, "POSITIVE": 1,"NEUTRAL":2}
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Nathamon/CommentwordExpo_Thai | Nathamon | 2023-11-02T08:17:12Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T08:17:12Z | 2023-11-02T08:17:11.000Z | 2023-11-02T08:17:11 | ---
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---
# Dataset Card for "CommentwordExpo_Thai"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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TrainingDataPro/computed-tomography-ct-of-the-abdomen | TrainingDataPro | 2023-11-02T08:31:10Z | 0 | 0 | null | [
"task_categories:image-classification",
"task_categories:image-to-image",
"task_categories:image-segmentation",
"language:en",
"license:cc-by-nc-nd-4.0",
"medical",
"code",
"region:us"
] | 2023-11-02T08:31:10Z | 2023-11-02T08:26:37.000Z | 2023-11-02T08:26:37 | ---
license: cc-by-nc-nd-4.0
task_categories:
- image-classification
- image-to-image
- image-segmentation
language:
- en
tags:
- medical
- code
---
# Computed Tomography (CT) of the Chest
The dataset contains a collection of CT (Computed Tomography) Abdomen scans in both **.jpg and .dcm** (DICOM) formats. These scans are used to capture detailed images of the abdominal region, providing insights into various **abdominal conditions and abnormalities**.
### Types of diseases and conditions in the dataset:
- **Abdominal aorta dilatation**
- **Aneurysmal dilatation of aorta**
- **Aortic aneurysm**
- **Cancer**
- **Formation of adrenal gland**
- **Kidney development**
- **Liver formation**
- **Urolithiasis**
- **Vertebral compression fracture**
The dataset provides a comprehensive dataset to study and develop algorithms or models for **automatic detection, classification, and treatment of various abdominal conditions and abnormalities**.
# Get the Dataset
## This is just an example of the data
Leave a request on [https://trainingdata.pro/data-market](https://trainingdata.pro/data-market/abdomen-pelvis-ct?utm_source=huggingface&utm_medium=cpc&utm_campaign=ct-of-the-abdomen) to discuss your requirements, learn about the price and buy the dataset
# Content
### The folder "files" includes 9 folders:
- corresponding to name of the disease and including ct scans of people with this disease (**abdominal aorta dilatation, aneurysmal dilatation of aorta, aortic aneurysm, cancer, formation of adrenal gland, kidney development, liver formation, urolithiasis and vertebral compression fracture**)
- including scans in 2 different formats: **.jpg and .dcm**.
### File with the extension .csv includes the following information for each media file:
- **dcm**: link to access the .dcm file,
- **jpg**: link to access the .jpg file,
- **type**: name of the disease on the ct
# Medical data might be collected in accordance with your requirements.
## [TrainingData](https://trainingdata.pro/data-market/abdomen-pelvis-ct?utm_source=huggingface&utm_medium=cpc&utm_campaign=ct-of-the-abdomen) provides high-quality data annotation tailored to your needs
More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets**
TrainingData's GitHub: **https://github.com/trainingdata-pro**
*keywords: ct abdomen scans, ct abdomen classification, ct abdomen detection, abdominal aorta dilatation, aneurysmal dilatation of aorta, aortic aneurysm, cancer dataset, formation of adrenal gland dataset, kidney development dataset, liver formation, urolithiasis, vertebral compression fracture, cancer detection, cancer segmentation, cancer classification, liver formation dataset* | [
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Zerenidel/DG-CS | Zerenidel | 2023-11-03T09:03:49Z | 0 | 0 | null | [
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Nathamon/CommentwordExpo_Eng-TH | Nathamon | 2023-11-02T11:15:39Z | 0 | 0 | null | [
"region:us"
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---
# Dataset Card for "CommentwordExpo_Eng-TH"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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berkouille/mistral_instruct_golf_dataset | berkouille | 2023-11-02T12:52:27Z | 0 | 0 | null | [
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Back-up/Topic-Prediction-Context | Back-up | 2023-11-02T13:20:42Z | 0 | 0 | null | [
"region:us"
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---
# Dataset Card for "Topic-Prediction-Context"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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SaffalPoosh/AN4_ASR_dataset | SaffalPoosh | 2023-11-02T15:08:20Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T15:08:20Z | 2023-11-02T13:55:30.000Z | 2023-11-02T13:55:30 | ---
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---
# Dataset Card for "AN4_ASR_dataset"
This dataset can be used to train NEMO English Speech models.
Audio files are sampled at `16kHz`.
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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alvarobartt/ultrafeedback-instruction-dataset-mini | alvarobartt | 2023-11-03T11:30:49Z | 0 | 0 | null | [
"region:us"
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---
# Dataset Card for "ultrafeedback-instruction-dataset-mini"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Back-up/Topic-Prediction-Context-With-Random-Prompts | Back-up | 2023-11-02T14:28:03Z | 0 | 0 | null | [
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---
# Dataset Card for "Topic-Prediction-Context-With-Random-Prompts"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Back-up/Topic-Prediction-Context-With-Random-Prompts-in-the-end | Back-up | 2023-11-02T14:48:54Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T14:48:54Z | 2023-11-02T14:48:47.000Z | 2023-11-02T14:48:47 | ---
dataset_info:
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struct:
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sequence: int64
- name: text
sequence: string
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splits:
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num_bytes: 248398
num_examples: 101
download_size: 125460
dataset_size: 248398
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "Topic-Prediction-Context-With-Random-Prompts-in-the-end"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Tonic/K23-Huggingface-Certificate-of-Excellence | Tonic | 2023-11-02T15:29:15Z | 0 | 0 | null | [
"language:en",
"license:apache-2.0",
"region:us"
] | 2023-11-02T15:29:15Z | 2023-11-02T15:28:00.000Z | 2023-11-02T15:28:00 | ---
license: apache-2.0
language:
- en
pretty_name: Certificate of Excellence
--- | [
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Back-up/Topic-Prediction-with-pair-qa-v1 | Back-up | 2023-11-02T15:32:12Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T15:32:12Z | 2023-11-02T15:32:07.000Z | 2023-11-02T15:32:07 | ---
configs:
- config_name: default
data_files:
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path: data/train-*
dataset_info:
features:
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dtype: string
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struct:
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splits:
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num_bytes: 153313
num_examples: 101
download_size: 82427
dataset_size: 153313
---
# Dataset Card for "Topic-Prediction-with-pair-qa-v1"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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JorJuz/JorJuz | JorJuz | 2023-11-02T15:36:32Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T15:36:32Z | 2023-11-02T15:36:10.000Z | 2023-11-02T15:36:10 | Entry not found | [
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patrickvonplaten/images_distil | patrickvonplaten | 2023-11-02T15:42:00Z | 0 | 0 | null | [
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] | 2023-11-02T15:42:00Z | 2023-11-02T15:37:07.000Z | 2023-11-02T15:37:07 | Entry not found | [
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herikhug/vozherik | herikhug | 2023-11-02T16:21:14Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T16:21:14Z | 2023-11-02T15:47:54.000Z | 2023-11-02T15:47:54 | Entry not found | [
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thangvip/OpenOrca-translate-openQA | thangvip | 2023-11-02T16:25:14Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T16:25:14Z | 2023-11-02T16:23:59.000Z | 2023-11-02T16:23:59 | Entry not found | [
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SouBryan/FNaF_Movie_William_Afton_in_Springbonnie_Suit | SouBryan | 2023-11-02T16:42:35Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | 2023-11-02T16:42:35Z | 2023-11-02T16:34:44.000Z | 2023-11-02T16:34:44 | ---
license: mit
---
| [
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Xapien/gpt4_pipe_test | Xapien | 2023-11-02T16:46:56Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T16:46:56Z | 2023-11-02T16:46:54.000Z | 2023-11-02T16:46:54 | ---
dataset_info:
features:
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splits:
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num_bytes: 2067
num_examples: 2
download_size: 8861
dataset_size: 2067
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "gpt4_pipe_test"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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automated-research-group/squad | automated-research-group | 2023-11-02T16:54:11Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T16:54:11Z | 2023-11-02T16:54:03.000Z | 2023-11-02T16:54:03 | ---
dataset_info:
features:
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sequence:
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dtype: int32
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dtype: string
splits:
- name: validation
num_bytes: 11802930
num_examples: 10570
download_size: 2657053
dataset_size: 11802930
configs:
- config_name: default
data_files:
- split: validation
path: data/validation-*
---
# Dataset Card for "squad"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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thangvip/webglm-data-100 | thangvip | 2023-11-02T17:29:19Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T17:29:19Z | 2023-11-02T17:17:14.000Z | 2023-11-02T17:17:14 | Entry not found | [
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ZenkoDraken/FNAF | ZenkoDraken | 2023-11-02T17:22:38Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T17:22:38Z | 2023-11-02T17:21:09.000Z | 2023-11-02T17:21:09 | Entry not found | [
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developer0313testing/meds | developer0313testing | 2023-11-02T17:25:58Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T17:25:58Z | 2023-11-02T17:24:33.000Z | 2023-11-02T17:24:33 | Entry not found | [
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... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
Fraternitas/out-of-scope | Fraternitas | 2023-11-03T00:47:43Z | 0 | 0 | null | [
"task_categories:text-classification",
"size_categories:10K<n<100K",
"language:en",
"region:us"
] | 2023-11-03T00:47:43Z | 2023-11-02T18:26:51.000Z | 2023-11-02T18:26:51 | ---
task_categories:
- text-classification
language:
- en
size_categories:
- 10K<n<100K
---
Here we can find the datasets generated to make a out-of-context classifier (ElektraGo Chat).
There are different version of the dataset:
- High Imbalanced
- Imbalanced
- Balanced (data augmentation and undersampling)
| [
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taesiri/twt-2021 | taesiri | 2023-11-03T04:17:24Z | 0 | 0 | null | [
"region:us"
] | 2023-11-03T04:17:24Z | 2023-11-02T18:55:49.000Z | 2023-11-02T18:55:49 | Entry not found | [
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... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
mabzak/id-politics-youtube-comment-21k | mabzak | 2023-11-02T19:08:46Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T19:08:46Z | 2023-11-02T19:05:59.000Z | 2023-11-02T19:05:59 | Entry not found | [
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... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
dhanush23/audio_dataset | dhanush23 | 2023-11-02T19:48:07Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T19:48:07Z | 2023-11-02T19:40:56.000Z | 2023-11-02T19:40:56 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: file_path
dtype: string
- name: emotion
dtype: string
splits:
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num_bytes: 312421.43086865044
num_examples: 4657
- name: test
num_bytes: 133971.56913134956
num_examples: 1997
download_size: 66671
dataset_size: 446393.0
---
# Dataset Card for "audio_dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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-0.3967985510826... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
Bsbell21/demodata1102 | Bsbell21 | 2023-11-02T20:51:19Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T20:51:19Z | 2023-11-02T20:51:18.000Z | 2023-11-02T20:51:18 | ---
dataset_info:
features:
- name: item
dtype: string
- name: description
dtype: string
- name: ad
dtype: string
splits:
- name: train
num_bytes: 1671
num_examples: 5
download_size: 4854
dataset_size: 1671
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "demodata1102"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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xxx4sharedxxx/ProgOOTryb | xxx4sharedxxx | 2023-11-02T21:46:30Z | 0 | 0 | null | [
"region:us"
] | 2023-11-02T21:46:30Z | 2023-11-02T21:02:25.000Z | 2023-11-02T21:02:25 | Entry not found | [
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... | null | null | null | null | null | null | null | null | null | null | null | null | null |
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