
# Dataset Card for dolly_tutorial

This dataset has been created with [Argilla](https://docs.argilla.io).

As shown in the sections below, this dataset can be loaded into Argilla as explained in [Load with Argilla](#load-with-argilla), or used directly with the `datasets` library in [Load with `datasets`](#load-with-datasets).

## Dataset Description

- **Homepage:** https://argilla.io
- **Repository:** https://github.com/argilla-io/argilla
- **Paper:** 
- **Leaderboard:** 
- **Point of Contact:** 

### Dataset Summary

This dataset contains:

* A dataset configuration file conforming to the Argilla dataset format named `argilla.yaml`. This configuration file will be used to configure the dataset when using the `FeedbackDataset.from_huggingface` method in Argilla.

* Dataset records in a format compatible with HuggingFace `datasets`. These records will be loaded automatically when using `FeedbackDataset.from_huggingface` and can be loaded independently using the `datasets` library via `load_dataset`.

* The [annotation guidelines](#annotation-guidelines) that have been used for building and curating the dataset, if they've been defined in Argilla.

### Load with Argilla

To load with Argilla, you'll just need to install Argilla as `pip install argilla --upgrade` and then use the following code:

```python
import argilla as rg

ds = rg.FeedbackDataset.from_huggingface("plaguss/dolly_tutorial")
```

### Load with `datasets`

To load this dataset with `datasets`, you'll just need to install `datasets` as `pip install datasets --upgrade` and then use the following code:

```python
from datasets import load_dataset

ds = load_dataset("plaguss/dolly_tutorial")
```

### Supported Tasks and Leaderboards

This dataset can contain [multiple fields, questions and responses](https://docs.argilla.io/en/latest/guides/llms/conceptual_guides/data_model.html) so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the [Dataset Structure section](#dataset-structure).

There are no leaderboards associated with this dataset.

### Languages

[More Information Needed]

## Dataset Structure

### Data in Argilla

The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, and **guidelines**.

The **fields** are the dataset records themselves, for the moment just text fields are suppported. These are the ones that will be used to provide responses to the questions.

| Field Name | Title | Type | Required | Markdown |
| ---------- | ----- | ---- | -------- | -------- |
| category | Task category | TextField | True | False |
| instruction | Instruction | TextField | True | False |
| context | Input | TextField | True | False |
| response | Response | TextField | True | False |


The **questions** are the questions that will be asked to the annotators. They can be of different types, such as rating, text, single choice, or multiple choice.

| Question Name | Title | Type | Required | Description | Values/Labels |
| ------------- | ----- | ---- | -------- | ----------- | ------------- |
| final-instruction | Final Instruction: | TextQuestion | True | desc instruction | N/A |
| final-context | Final Input: | TextQuestion | True | desc input | N/A |
| final-response | Final Response: | TextQuestion | True | desc response | N/A |


**✨ NEW** Additionally, we also have **suggestions**, which are linked to the existing questions, and so on, named appending "-suggestion" and "-suggestion-metadata" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above.

Finally, the **guidelines** are just a plain string that can be used to provide instructions to the annotators. Find those in the [annotation guidelines](#annotation-guidelines) section.

### Data Instances

An example of a dataset instance in Argilla looks as follows:

```json
{
    "external_id": "6",
    "fields": {
        "category": "closed_qa",
        "context": "Lollapalooza /\u02ccl\u0252l\u0259p\u0259\u02c8lu\u02d0z\u0259/ (Lolla) is an annual American four-day music festival held in Grant Park in Chicago. It originally started as a touring event in 1991, but several years later, Chicago became its permanent location. Music genres include but are not limited to alternative rock, heavy metal, punk rock, hip hop, and electronic dance music. Lollapalooza has also featured visual arts, nonprofit organizations, and political organizations. The festival, held in Grant Park, hosts an estimated 400,000 people each July and sells out annually. Lollapalooza is one of the largest and most iconic music festivals in the world and one of the longest-running in the United States.\n\nLollapalooza was conceived and created in 1991 as a farewell tour by Perry Farrell, singer of the group Jane\u0027s Addiction.",
        "instruction": "Given a reference text about Lollapalooza, where does it take place, who started it and what is it?",
        "response": "Lollapalooze is an annual musical festival held in Grant Park in Chicago, Illinois. It was started in 1991 as a farewell tour by Perry Farrell, singe of the group Jane\u0027s Addiction. The festival includes an array of musical genres including alternative rock, heavy metal, punk rock, hip hop, and electronic dance music. The festivals welcomes an estimated 400,000 people each year and sells out annually. Some notable headliners include: the Red Hot Chili Peppers, Chance the Rapper, Metallica, and Lady Gage. Lollapalooza is one of the largest and most iconic festivals in the world and a staple of Chicago."
    },
    "id": "19ffb042-93f9-4402-9418-1671c5c081d7",
    "metadata": {},
    "responses": [],
    "suggestions": []
}
```

While the same record in HuggingFace `datasets` looks as follows:

```json
{
    "category": "closed_qa",
    "context": "Lollapalooza /\u02ccl\u0252l\u0259p\u0259\u02c8lu\u02d0z\u0259/ (Lolla) is an annual American four-day music festival held in Grant Park in Chicago. It originally started as a touring event in 1991, but several years later, Chicago became its permanent location. Music genres include but are not limited to alternative rock, heavy metal, punk rock, hip hop, and electronic dance music. Lollapalooza has also featured visual arts, nonprofit organizations, and political organizations. The festival, held in Grant Park, hosts an estimated 400,000 people each July and sells out annually. Lollapalooza is one of the largest and most iconic music festivals in the world and one of the longest-running in the United States.\n\nLollapalooza was conceived and created in 1991 as a farewell tour by Perry Farrell, singer of the group Jane\u0027s Addiction.",
    "external_id": "6",
    "final-context": null,
    "final-context-suggestion": null,
    "final-context-suggestion-metadata": {
        "agent": null,
        "score": null,
        "type": null
    },
    "final-instruction": null,
    "final-instruction-suggestion": null,
    "final-instruction-suggestion-metadata": {
        "agent": null,
        "score": null,
        "type": null
    },
    "final-response": null,
    "final-response-suggestion": null,
    "final-response-suggestion-metadata": {
        "agent": null,
        "score": null,
        "type": null
    },
    "instruction": "Given a reference text about Lollapalooza, where does it take place, who started it and what is it?",
    "metadata": null,
    "response": "Lollapalooze is an annual musical festival held in Grant Park in Chicago, Illinois. It was started in 1991 as a farewell tour by Perry Farrell, singe of the group Jane\u0027s Addiction. The festival includes an array of musical genres including alternative rock, heavy metal, punk rock, hip hop, and electronic dance music. The festivals welcomes an estimated 400,000 people each year and sells out annually. Some notable headliners include: the Red Hot Chili Peppers, Chance the Rapper, Metallica, and Lady Gage. Lollapalooza is one of the largest and most iconic festivals in the world and a staple of Chicago."
}
```

### Data Fields

Among the dataset fields, we differentiate between the following:

* **Fields:** These are the dataset records themselves, for the moment just text fields are suppported. These are the ones that will be used to provide responses to the questions.
    
    * **category** is of type `TextField`.
    * **instruction** is of type `TextField`.
    * (optional) **context** is of type `TextField`.
    * **response** is of type `TextField`.

* **Questions:** These are the questions that will be asked to the annotators. They can be of different types, such as `RatingQuestion`, `TextQuestion`, `LabelQuestion`, `MultiLabelQuestion`, and `RankingQuestion`.
    
    * **final-instruction** is of type `TextQuestion`, and description "desc instruction".
    * (optional) **final-context** is of type `TextQuestion`, and description "desc input".
    * **final-response** is of type `TextQuestion`, and description "desc response".

* **✨ NEW** **Suggestions:** As of Argilla 1.13.0, the suggestions have been included to provide the annotators with suggestions to ease or assist during the annotation process. Suggestions are linked to the existing questions, are always optional, and contain not just the suggestion itself, but also the metadata linked to it, if applicable.
    
    * (optional) **final-instruction-suggestion** is of type `text`.
    * (optional) **final-context-suggestion** is of type `text`.
    * (optional) **final-response-suggestion** is of type `text`.

Additionally, we also have one more field which is optional and is the following:

* **external_id:** This is an optional field that can be used to provide an external ID for the dataset record. This can be useful if you want to link the dataset record to an external resource, such as a database or a file.

### Data Splits

The dataset contains a single split, which is `train`.

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation guidelines

our guidelines

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information

[More Information Needed]

### Contributions

[More Information Needed]
size_categories:10K<n<100K rlfh argilla human-feedback region:us
{"size_categories": "10K<n<100K", "tags": ["rlfh", "argilla", "human-feedback"]}
TAGS
#size_categories-10K<n<100K #rlfh #argilla #human-feedback #region-us 

Dataset Card for dolly\_tutorial
================================


This dataset has been created with Argilla.


As shown in the sections below, this dataset can be loaded into Argilla as explained in Load with Argilla, or used directly with the 'datasets' library in Load with 'datasets'.


Dataset Description
-------------------


* Homepage: URL
* Repository: URL
* Paper:
* Leaderboard:
* Point of Contact:


### Dataset Summary


This dataset contains:


* A dataset configuration file conforming to the Argilla dataset format named 'URL'. This configuration file will be used to configure the dataset when using the 'FeedbackDataset.from\_huggingface' method in Argilla.
* Dataset records in a format compatible with HuggingFace 'datasets'. These records will be loaded automatically when using 'FeedbackDataset.from\_huggingface' and can be loaded independently using the 'datasets' library via 'load\_dataset'.
* The annotation guidelines that have been used for building and curating the dataset, if they've been defined in Argilla.


### Load with Argilla


To load with Argilla, you'll just need to install Argilla as 'pip install argilla --upgrade' and then use the following code:


### Load with 'datasets'


To load this dataset with 'datasets', you'll just need to install 'datasets' as 'pip install datasets --upgrade' and then use the following code:


### Supported Tasks and Leaderboards


This dataset can contain multiple fields, questions and responses so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the Dataset Structure section.


There are no leaderboards associated with this dataset.


### Languages


Dataset Structure
-----------------


### Data in Argilla


The dataset is created in Argilla with: fields, questions, suggestions, and guidelines.


The fields are the dataset records themselves, for the moment just text fields are suppported. These are the ones that will be used to provide responses to the questions.



The questions are the questions that will be asked to the annotators. They can be of different types, such as rating, text, single choice, or multiple choice.



NEW Additionally, we also have suggestions, which are linked to the existing questions, and so on, named appending "-suggestion" and "-suggestion-metadata" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above.


Finally, the guidelines are just a plain string that can be used to provide instructions to the annotators. Find those in the annotation guidelines section.


### Data Instances


An example of a dataset instance in Argilla looks as follows:


While the same record in HuggingFace 'datasets' looks as follows:


### Data Fields


Among the dataset fields, we differentiate between the following:


* Fields: These are the dataset records themselves, for the moment just text fields are suppported. These are the ones that will be used to provide responses to the questions.


	+ category is of type 'TextField'.
	+ instruction is of type 'TextField'.
	+ (optional) context is of type 'TextField'.
	+ response is of type 'TextField'.
* Questions: These are the questions that will be asked to the annotators. They can be of different types, such as 'RatingQuestion', 'TextQuestion', 'LabelQuestion', 'MultiLabelQuestion', and 'RankingQuestion'.


	+ final-instruction is of type 'TextQuestion', and description "desc instruction".
	+ (optional) final-context is of type 'TextQuestion', and description "desc input".
	+ final-response is of type 'TextQuestion', and description "desc response".
* NEW Suggestions: As of Argilla 1.13.0, the suggestions have been included to provide the annotators with suggestions to ease or assist during the annotation process. Suggestions are linked to the existing questions, are always optional, and contain not just the suggestion itself, but also the metadata linked to it, if applicable.


	+ (optional) final-instruction-suggestion is of type 'text'.
	+ (optional) final-context-suggestion is of type 'text'.
	+ (optional) final-response-suggestion is of type 'text'.


Additionally, we also have one more field which is optional and is the following:


* external\_id: This is an optional field that can be used to provide an external ID for the dataset record. This can be useful if you want to link the dataset record to an external resource, such as a database or a file.


### Data Splits


The dataset contains a single split, which is 'train'.


Dataset Creation
----------------


### Curation Rationale


### Source Data


#### Initial Data Collection and Normalization


#### Who are the source language producers?


### Annotations


#### Annotation guidelines


our guidelines


#### Annotation process


#### Who are the annotators?


### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------


### Social Impact of Dataset


### Discussion of Biases


### Other Known Limitations


Additional Information
----------------------


### Dataset Curators


### Licensing Information


### Contributions



### Dataset Summary


This dataset contains:


* A dataset configuration file conforming to the Argilla dataset format named 'URL'. This configuration file will be used to configure the dataset when using the 'FeedbackDataset.from\_huggingface' method in Argilla.
* Dataset records in a format compatible with HuggingFace 'datasets'. These records will be loaded automatically when using 'FeedbackDataset.from\_huggingface' and can be loaded independently using the 'datasets' library via 'load\_dataset'.
* The annotation guidelines that have been used for building and curating the dataset, if they've been defined in Argilla. ### Load with Argilla


To load with Argilla, you'll just need to install Argilla as 'pip install argilla --upgrade' and then use the following code: ### Load with 'datasets'


To load this dataset with 'datasets', you'll just need to install 'datasets' as 'pip install datasets --upgrade' and then use the following code: ### Supported Tasks and Leaderboards


This dataset can contain multiple fields, questions and responses so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the Dataset Structure section.


There are no leaderboards associated with this dataset. ### Languages


Dataset Structure
----------------- ### Data in Argilla


The dataset is created in Argilla with: fields, questions, suggestions, and guidelines.


The fields are the dataset records themselves, for the moment just text fields are suppported. These are the ones that will be used to provide responses to the questions.



The questions are the questions that will be asked to the annotators. They can be of different types, such as rating, text, single choice, or multiple choice.



NEW Additionally, we also have suggestions, which are linked to the existing questions, and so on, named appending "-suggestion" and "-suggestion-metadata" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above.


Finally, the guidelines are just a plain string that can be used to provide instructions to the annotators. Find those in the annotation guidelines section. ### Data Instances


An example of a dataset instance in Argilla looks as follows:


While the same record in HuggingFace 'datasets' looks as follows: ### Data Fields


Among the dataset fields, we differentiate between the following:


* Fields: These are the dataset records themselves, for the moment just text fields are suppported. These are the ones that will be used to provide responses to the questions.


	+ category is of type 'TextField'.
	+ instruction is of type 'TextField'.
	+ (optional) context is of type 'TextField'.
	+ response is of type 'TextField'.
* Questions: These are the questions that will be asked to the annotators. They can be of different types, such as 'RatingQuestion', 'TextQuestion', 'LabelQuestion', 'MultiLabelQuestion', and 'RankingQuestion'.


	+ final-instruction is of type 'TextQuestion', and description "desc instruction".
	+ (optional) final-context is of type 'TextQuestion', and description "desc input".
	+ final-response is of type 'TextQuestion', and description "desc response".
* NEW Suggestions: As of Argilla 1.13.0, the suggestions have been included to provide the annotators with suggestions to ease or assist during the annotation process. Suggestions are linked to the existing questions, are always optional, and contain not just the suggestion itself, but also the metadata linked to it, if applicable.


	+ (optional) final-instruction-suggestion is of type 'text'.
	+ (optional) final-context-suggestion is of type 'text'.
	+ (optional) final-response-suggestion is of type 'text'.


Additionally, we also have one more field which is optional and is the following:


* external\_id: This is an optional field that can be used to provide an external ID for the dataset record. This can be useful if you want to link the dataset record to an external resource, such as a database or a file. ### Data Splits


The dataset contains a single split, which is 'train'.


Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation guidelines


our guidelines #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information ### Contributions
TAGS
#size_categories-10K<n<100K #rlfh #argilla #human-feedback #region-us 
 ### Dataset Summary


This dataset contains:


* A dataset configuration file conforming to the Argilla dataset format named 'URL'. This configuration file will be used to configure the dataset when using the 'FeedbackDataset.from\_huggingface' method in Argilla.
* Dataset records in a format compatible with HuggingFace 'datasets'. These records will be loaded automatically when using 'FeedbackDataset.from\_huggingface' and can be loaded independently using the 'datasets' library via 'load\_dataset'.
* The annotation guidelines that have been used for building and curating the dataset, if they've been defined in Argilla. ### Load with Argilla


To load with Argilla, you'll just need to install Argilla as 'pip install argilla --upgrade' and then use the following code: ### Load with 'datasets'


To load this dataset with 'datasets', you'll just need to install 'datasets' as 'pip install datasets --upgrade' and then use the following code: ### Supported Tasks and Leaderboards


This dataset can contain multiple fields, questions and responses so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the Dataset Structure section.


There are no leaderboards associated with this dataset. ### Languages


Dataset Structure
----------------- ### Data in Argilla


The dataset is created in Argilla with: fields, questions, suggestions, and guidelines.


The fields are the dataset records themselves, for the moment just text fields are suppported. These are the ones that will be used to provide responses to the questions.



The questions are the questions that will be asked to the annotators. They can be of different types, such as rating, text, single choice, or multiple choice.



NEW Additionally, we also have suggestions, which are linked to the existing questions, and so on, named appending "-suggestion" and "-suggestion-metadata" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above.


Finally, the guidelines are just a plain string that can be used to provide instructions to the annotators. Find those in the annotation guidelines section. ### Data Instances


An example of a dataset instance in Argilla looks as follows:


While the same record in HuggingFace 'datasets' looks as follows: ### Data Fields


Among the dataset fields, we differentiate between the following:


* Fields: These are the dataset records themselves, for the moment just text fields are suppported. These are the ones that will be used to provide responses to the questions.


	+ category is of type 'TextField'.
	+ instruction is of type 'TextField'.
	+ (optional) context is of type 'TextField'.
	+ response is of type 'TextField'.
* Questions: These are the questions that will be asked to the annotators. They can be of different types, such as 'RatingQuestion', 'TextQuestion', 'LabelQuestion', 'MultiLabelQuestion', and 'RankingQuestion'.


	+ final-instruction is of type 'TextQuestion', and description "desc instruction".
	+ (optional) final-context is of type 'TextQuestion', and description "desc input".
	+ final-response is of type 'TextQuestion', and description "desc response".
* NEW Suggestions: As of Argilla 1.13.0, the suggestions have been included to provide the annotators with suggestions to ease or assist during the annotation process. Suggestions are linked to the existing questions, are always optional, and contain not just the suggestion itself, but also the metadata linked to it, if applicable.


	+ (optional) final-instruction-suggestion is of type 'text'.
	+ (optional) final-context-suggestion is of type 'text'.
	+ (optional) final-response-suggestion is of type 'text'.


Additionally, we also have one more field which is optional and is the following:


* external\_id: This is an optional field that can be used to provide an external ID for the dataset record. This can be useful if you want to link the dataset record to an external resource, such as a database or a file. ### Data Splits


The dataset contains a single split, which is 'train'.


Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation guidelines


our guidelines #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information ### Contributions
passage: TAGS
#size_categories-10K<n<100K #rlfh #argilla #human-feedback #region-us 
### Dataset Summary


This dataset contains:


* A dataset configuration file conforming to the Argilla dataset format named 'URL'. This configuration file will be used to configure the dataset when using the 'FeedbackDataset.from\_huggingface' method in Argilla.
* Dataset records in a format compatible with HuggingFace 'datasets'. These records will be loaded automatically when using 'FeedbackDataset.from\_huggingface' and can be loaded independently using the 'datasets' library via 'load\_dataset'.
* The annotation guidelines that have been used for building and curating the dataset, if they've been defined in Argilla.### Load with Argilla


To load with Argilla, you'll just need to install Argilla as 'pip install argilla --upgrade' and then use the following code:### Load with 'datasets'


To load this dataset with 'datasets', you'll just need to install 'datasets' as 'pip install datasets --upgrade' and then use the following code:### Supported Tasks and Leaderboards


This dataset can contain multiple fields, questions and responses so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the Dataset Structure section.


There are no leaderboards associated with this dataset.### Languages


Dataset Structure
----------------- passage: ### Data in Argilla


The dataset is created in Argilla with: fields, questions, suggestions, and guidelines.


The fields are the dataset records themselves, for the moment just text fields are suppported. These are the ones that will be used to provide responses to the questions.



The questions are the questions that will be asked to the annotators. They can be of different types, such as rating, text, single choice, or multiple choice.



NEW Additionally, we also have suggestions, which are linked to the existing questions, and so on, named appending "-suggestion" and "-suggestion-metadata" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above.


Finally, the guidelines are just a plain string that can be used to provide instructions to the annotators. Find those in the annotation guidelines section.### Data Instances


An example of a dataset instance in Argilla looks as follows:


While the same record in HuggingFace 'datasets' looks as follows:### Data Fields


Among the dataset fields, we differentiate between the following:


* Fields: These are the dataset records themselves, for the moment just text fields are suppported. These are the ones that will be used to provide responses to the questions.


	+ category is of type 'TextField'.
	+ instruction is of type 'TextField'.
	+ (optional) context is of type 'TextField'.
	+ response is of type 'TextField'.
* Questions: These are the questions that will be asked to the annotators. They can be of different types, such as 'RatingQuestion', 'TextQuestion', 'LabelQuestion', 'MultiLabelQuestion', and 'RankingQuestion'.


	+ final-instruction is of type 'TextQuestion', and description "desc instruction".
	+ (optional) final-context is of type 'TextQuestion', and description "desc input".
	+ final-response is of type 'TextQuestion', and description "desc response".
* NEW Suggestions: As of Argilla 1.13.0, the suggestions have been included to provide the annotators with suggestions to ease or assist during the annotation process. Suggestions are linked to the existing questions, are always optional, and contain not just the suggestion itself, but also the metadata linked to it, if applicable.


	+ (optional) final-instruction-suggestion is of type 'text'.
	+ (optional) final-context-suggestion is of type 'text'.
	+ (optional) final-response-suggestion is of type 'text'.


Additionally, we also have one more field which is optional and is the following:


* external\_id: This is an optional field that can be used to provide an external ID for the dataset record. This can be useful if you want to link the dataset record to an external resource, such as a database or a file.