## 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-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)

## Dataset Description

### Dataset Summary

LawyerChat is a multi-turn conversational dataset primarily in the English language, containing dialogues about legal scenarios. The conversations are in the format of an interaction between a client and a legal professional. The dataset is designed for training and evaluating models on conversational tasks like dialogue understanding, response generation, and more.

### Supported Tasks and Leaderboards

- `dialogue-modeling`: The dataset can be used to train a model for multi-turn dialogue understanding and generation. Performance can be evaluated based on dialogue understanding and the quality of the generated responses.
- There is no official leaderboard associated with this dataset at this time.

dataset generated in part by  dang/futures 
### Languages

The text in the dataset is in English.

## Dataset Structure

### Data Instances

An instance in the LawyerChat dataset represents a single turn in a conversation, consisting of a user id and their corresponding utterance. Example:

```json
{
"conversations": [
{
"from": "user_id_1",
"value": "What are the possible legal consequences of not paying taxes?"
},
{
"from": "user_id_2",
"value": "There can be several legal consequences, ranging from fines to imprisonment..."
},
...
]
}
license:apache-2.0 region:us
{"license": "apache-2.0"}
TAGS
#license-apache-2.0 #region-us 

## Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits

## Dataset Description

### Dataset Summary

LawyerChat is a multi-turn conversational dataset primarily in the English language, containing dialogues about legal scenarios. The conversations are in the format of an interaction between a client and a legal professional. The dataset is designed for training and evaluating models on conversational tasks like dialogue understanding, response generation, and more.

### Supported Tasks and Leaderboards

- 'dialogue-modeling': The dataset can be used to train a model for multi-turn dialogue understanding and generation. Performance can be evaluated based on dialogue understanding and the quality of the generated responses.
- There is no official leaderboard associated with this dataset at this time.

dataset generated in part by  dang/futures 
### Languages

The text in the dataset is in English.

## Dataset Structure

### Data Instances

An instance in the LawyerChat dataset represents a single turn in a conversation, consisting of a user id and their corresponding utterance. Example:

'''json
{
"conversations": [
{
"from": "user_id_1",
"value": "What are the possible legal consequences of not paying taxes?"
},
{
"from": "user_id_2",
"value": "There can be several legal consequences, ranging from fines to imprisonment..."
},
...
]
}
## Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits ## Dataset Description ### Dataset Summary

LawyerChat is a multi-turn conversational dataset primarily in the English language, containing dialogues about legal scenarios. The conversations are in the format of an interaction between a client and a legal professional. The dataset is designed for training and evaluating models on conversational tasks like dialogue understanding, response generation, and more. ### Supported Tasks and Leaderboards

- 'dialogue-modeling': The dataset can be used to train a model for multi-turn dialogue understanding and generation. Performance can be evaluated based on dialogue understanding and the quality of the generated responses.
- There is no official leaderboard associated with this dataset at this time.

dataset generated in part by  dang/futures ### Languages

The text in the dataset is in English. ## Dataset Structure ### Data Instances

An instance in the LawyerChat dataset represents a single turn in a conversation, consisting of a user id and their corresponding utterance. Example:

'''json
{
"conversations": [
{
"from": "user_id_1",
"value": "What are the possible legal consequences of not paying taxes?"
},
{
"from": "user_id_2",
"value": "There can be several legal consequences, ranging from fines to imprisonment..."
},
...
]
}
TAGS
#license-apache-2.0 #region-us 
 ## Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits ## Dataset Description ### Dataset Summary

LawyerChat is a multi-turn conversational dataset primarily in the English language, containing dialogues about legal scenarios. The conversations are in the format of an interaction between a client and a legal professional. The dataset is designed for training and evaluating models on conversational tasks like dialogue understanding, response generation, and more. ### Supported Tasks and Leaderboards

- 'dialogue-modeling': The dataset can be used to train a model for multi-turn dialogue understanding and generation. Performance can be evaluated based on dialogue understanding and the quality of the generated responses.
- There is no official leaderboard associated with this dataset at this time.

dataset generated in part by  dang/futures ### Languages

The text in the dataset is in English. ## Dataset Structure ### Data Instances

An instance in the LawyerChat dataset represents a single turn in a conversation, consisting of a user id and their corresponding utterance. Example:

'''json
{
"conversations": [
{
"from": "user_id_1",
"value": "What are the possible legal consequences of not paying taxes?"
},
{
"from": "user_id_2",
"value": "There can be several legal consequences, ranging from fines to imprisonment..."
},
...
]
}
passage: TAGS
#license-apache-2.0 #region-us 
## Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits## Dataset Description### Dataset Summary

LawyerChat is a multi-turn conversational dataset primarily in the English language, containing dialogues about legal scenarios. The conversations are in the format of an interaction between a client and a legal professional. The dataset is designed for training and evaluating models on conversational tasks like dialogue understanding, response generation, and more.### Supported Tasks and Leaderboards

- 'dialogue-modeling': The dataset can be used to train a model for multi-turn dialogue understanding and generation. Performance can be evaluated based on dialogue understanding and the quality of the generated responses.
- There is no official leaderboard associated with this dataset at this time.

dataset generated in part by  dang/futures### Languages

The text in the dataset is in English.## Dataset Structure### Data Instances

An instance in the LawyerChat dataset represents a single turn in a conversation, consisting of a user id and their corresponding utterance. Example:

'''json
{
"conversations": [
{
"from": "user_id_1",
"value": "What are the possible legal consequences of not paying taxes?"
},
{
"from": "user_id_2",
"value": "There can be several legal consequences, ranging from fines to imprisonment..."
},
...
]
}