# Alpaca-like Model Training Dataset Generated from GPT-3.5

This dataset contains 56,000+ samples generated from GPT-3.5 and extreme content filtering removed and replaced with relevant generated outputs. Specifically designed for training Alpaca-like models. Each sample includes an instruction, an optional input text, and an output text.

## Dataset Description

The dataset is a collection of diverse tasks and prompts that are suited for training and fine-tuning Alpaca-like language models. It includes a wide variety of tasks such as text summarization, question-answering, translation, and more. The dataset has been generated using GPT-3.5, which provides high-quality samples.

### Data Format

Each sample in the dataset is represented as a JSON object with the following structure:

```json
{
  "instruction": "string",
  "input": "string",
  "output": "string"
}

instruction: A text string that provides the instruction for the task. It can be a question, a prompt, or a description of the desired output.
input: An optional text string that provides the input for the task. It can be a text passage, a set of questions, or any other relevant information for the task. If there is no specific input, this field is empty.
output: A text string that provides the output generated by GPT-3.5 in response to the instruction and input.
Dataset Usage
This dataset can be used for various natural language understanding and generation tasks, including but not limited to:

Training and fine-tuning Alpaca-like language models.
Evaluating the performance of pre-trained models on diverse tasks.
Exploring the capabilities and limitations of GPT-3.5 generated samples.
Conducting research on transfer learning and few-shot learning in NLP.

Free for all.

If you want to follow me you can @WoodnBarrlGame on twitter. 
license:apache-2.0 region:us
{"license": "apache-2.0"}
TAGS
#license-apache-2.0 #region-us 

# Alpaca-like Model Training Dataset Generated from GPT-3.5

This dataset contains 56,000+ samples generated from GPT-3.5 and extreme content filtering removed and replaced with relevant generated outputs. Specifically designed for training Alpaca-like models. Each sample includes an instruction, an optional input text, and an output text.

## Dataset Description

The dataset is a collection of diverse tasks and prompts that are suited for training and fine-tuning Alpaca-like language models. It includes a wide variety of tasks such as text summarization, question-answering, translation, and more. The dataset has been generated using GPT-3.5, which provides high-quality samples.

### Data Format

Each sample in the dataset is represented as a JSON object with the following structure:

'''json
{
  "instruction": "string",
  "input": "string",
  "output": "string"
}

instruction: A text string that provides the instruction for the task. It can be a question, a prompt, or a description of the desired output.
input: An optional text string that provides the input for the task. It can be a text passage, a set of questions, or any other relevant information for the task. If there is no specific input, this field is empty.
output: A text string that provides the output generated by GPT-3.5 in response to the instruction and input.
Dataset Usage
This dataset can be used for various natural language understanding and generation tasks, including but not limited to:

Training and fine-tuning Alpaca-like language models.
Evaluating the performance of pre-trained models on diverse tasks.
Exploring the capabilities and limitations of GPT-3.5 generated samples.
Conducting research on transfer learning and few-shot learning in NLP.

Free for all.

If you want to follow me you can @WoodnBarrlGame on twitter. 
# Alpaca-like Model Training Dataset Generated from GPT-3.5

This dataset contains 56,000+ samples generated from GPT-3.5 and extreme content filtering removed and replaced with relevant generated outputs. Specifically designed for training Alpaca-like models. Each sample includes an instruction, an optional input text, and an output text. ## Dataset Description

The dataset is a collection of diverse tasks and prompts that are suited for training and fine-tuning Alpaca-like language models. It includes a wide variety of tasks such as text summarization, question-answering, translation, and more. The dataset has been generated using GPT-3.5, which provides high-quality samples. ### Data Format

Each sample in the dataset is represented as a JSON object with the following structure:

'''json
{
  "instruction": "string",
  "input": "string",
  "output": "string"
}

instruction: A text string that provides the instruction for the task. It can be a question, a prompt, or a description of the desired output.
input: An optional text string that provides the input for the task. It can be a text passage, a set of questions, or any other relevant information for the task. If there is no specific input, this field is empty.
output: A text string that provides the output generated by GPT-3.5 in response to the instruction and input.
Dataset Usage
This dataset can be used for various natural language understanding and generation tasks, including but not limited to:

Training and fine-tuning Alpaca-like language models.
Evaluating the performance of pre-trained models on diverse tasks.
Exploring the capabilities and limitations of GPT-3.5 generated samples.
Conducting research on transfer learning and few-shot learning in NLP.

Free for all.

If you want to follow me you can @WoodnBarrlGame on twitter.
TAGS
#license-apache-2.0 #region-us 
 # Alpaca-like Model Training Dataset Generated from GPT-3.5

This dataset contains 56,000+ samples generated from GPT-3.5 and extreme content filtering removed and replaced with relevant generated outputs. Specifically designed for training Alpaca-like models. Each sample includes an instruction, an optional input text, and an output text. ## Dataset Description

The dataset is a collection of diverse tasks and prompts that are suited for training and fine-tuning Alpaca-like language models. It includes a wide variety of tasks such as text summarization, question-answering, translation, and more. The dataset has been generated using GPT-3.5, which provides high-quality samples. ### Data Format

Each sample in the dataset is represented as a JSON object with the following structure:

'''json
{
  "instruction": "string",
  "input": "string",
  "output": "string"
}

instruction: A text string that provides the instruction for the task. It can be a question, a prompt, or a description of the desired output.
input: An optional text string that provides the input for the task. It can be a text passage, a set of questions, or any other relevant information for the task. If there is no specific input, this field is empty.
output: A text string that provides the output generated by GPT-3.5 in response to the instruction and input.
Dataset Usage
This dataset can be used for various natural language understanding and generation tasks, including but not limited to:

Training and fine-tuning Alpaca-like language models.
Evaluating the performance of pre-trained models on diverse tasks.
Exploring the capabilities and limitations of GPT-3.5 generated samples.
Conducting research on transfer learning and few-shot learning in NLP.

Free for all.

If you want to follow me you can @WoodnBarrlGame on twitter.
passage: TAGS
#license-apache-2.0 #region-us 
# Alpaca-like Model Training Dataset Generated from GPT-3.5

This dataset contains 56,000+ samples generated from GPT-3.5 and extreme content filtering removed and replaced with relevant generated outputs. Specifically designed for training Alpaca-like models. Each sample includes an instruction, an optional input text, and an output text.## Dataset Description

The dataset is a collection of diverse tasks and prompts that are suited for training and fine-tuning Alpaca-like language models. It includes a wide variety of tasks such as text summarization, question-answering, translation, and more. The dataset has been generated using GPT-3.5, which provides high-quality samples.### Data Format

Each sample in the dataset is represented as a JSON object with the following structure:

'''json
{
  "instruction": "string",
  "input": "string",
  "output": "string"
}

instruction: A text string that provides the instruction for the task. It can be a question, a prompt, or a description of the desired output.
input: An optional text string that provides the input for the task. It can be a text passage, a set of questions, or any other relevant information for the task. If there is no specific input, this field is empty.
output: A text string that provides the output generated by GPT-3.5 in response to the instruction and input.
Dataset Usage
This dataset can be used for various natural language understanding and generation tasks, including but not limited to:

Training and fine-tuning Alpaca-like language models.
Evaluating the performance of pre-trained models on diverse tasks.
Exploring the capabilities and limitations of GPT-3.5 generated samples.
Conducting research on transfer learning and few-shot learning in NLP.

Free for all.

If you want to follow me you can @WoodnBarrlGame on twitter.