
# EverythingLM Dataset

**EverythingLM** is a diverse instruct dataset consisting of ~1k sets of system prompts, instructions, and corresponding responses. These sets were generated using principles from both evol-instruct and Orca. The dataset encompasses a wide array of topics and interactions.
### Categories:

- Reasoning
- Creative Writing
- General Knowledge
- Brainstorming
- Search Query
- Coding
- Basic Instruct

We also leverage various system prompts for evol-instruct and for responding to prompts.
This dataset has also been filtered to remove OpenAI alignment.

### How it stands out:

- Long, detailed outputs
- Humanlike creativity
- CoT reasoning
- Complex & challenging tasks

### Plans:

- Train Llama 7b & 13b models
- Train Llama 70b QLoRA
- Generate V2 of the dataset, with more categories and GPT-4

### How does it work?

1. Generate list of categories, prompts, sysprompts, etc (human)
2. Generate seed prompts (GPT)
3. Evolve prompts (GPT)
4. Generate responses (GPT)
5. Convert to Alpaca dataset format

Included in this repo is the script to generate the dataset.  However, it is buggy and probably not the best implementation possible.
license:mit region:us
{"license": "mit"}
TAGS
#license-mit #region-us 


# EverythingLM Dataset

EverythingLM is a diverse instruct dataset consisting of ~1k sets of system prompts, instructions, and corresponding responses. These sets were generated using principles from both evol-instruct and Orca. The dataset encompasses a wide array of topics and interactions.
### Categories:

- Reasoning
- Creative Writing
- General Knowledge
- Brainstorming
- Search Query
- Coding
- Basic Instruct

We also leverage various system prompts for evol-instruct and for responding to prompts.
This dataset has also been filtered to remove OpenAI alignment.

### How it stands out:

- Long, detailed outputs
- Humanlike creativity
- CoT reasoning
- Complex & challenging tasks

### Plans:

- Train Llama 7b & 13b models
- Train Llama 70b QLoRA
- Generate V2 of the dataset, with more categories and GPT-4

### How does it work?

1. Generate list of categories, prompts, sysprompts, etc (human)
2. Generate seed prompts (GPT)
3. Evolve prompts (GPT)
4. Generate responses (GPT)
5. Convert to Alpaca dataset format

Included in this repo is the script to generate the dataset.  However, it is buggy and probably not the best implementation possible.
# EverythingLM Dataset

EverythingLM is a diverse instruct dataset consisting of ~1k sets of system prompts, instructions, and corresponding responses. These sets were generated using principles from both evol-instruct and Orca. The dataset encompasses a wide array of topics and interactions. ### Categories:

- Reasoning
- Creative Writing
- General Knowledge
- Brainstorming
- Search Query
- Coding
- Basic Instruct

We also leverage various system prompts for evol-instruct and for responding to prompts.
This dataset has also been filtered to remove OpenAI alignment. ### How it stands out:

- Long, detailed outputs
- Humanlike creativity
- CoT reasoning
- Complex & challenging tasks ### Plans:

- Train Llama 7b & 13b models
- Train Llama 70b QLoRA
- Generate V2 of the dataset, with more categories and GPT-4 ### How does it work?

1. Generate list of categories, prompts, sysprompts, etc (human)
2. Generate seed prompts (GPT)
3. Evolve prompts (GPT)
4. Generate responses (GPT)
5. Convert to Alpaca dataset format

Included in this repo is the script to generate the dataset.  However, it is buggy and probably not the best implementation possible.
TAGS
#license-mit #region-us 
 # EverythingLM Dataset

EverythingLM is a diverse instruct dataset consisting of ~1k sets of system prompts, instructions, and corresponding responses. These sets were generated using principles from both evol-instruct and Orca. The dataset encompasses a wide array of topics and interactions. ### Categories:

- Reasoning
- Creative Writing
- General Knowledge
- Brainstorming
- Search Query
- Coding
- Basic Instruct

We also leverage various system prompts for evol-instruct and for responding to prompts.
This dataset has also been filtered to remove OpenAI alignment. ### How it stands out:

- Long, detailed outputs
- Humanlike creativity
- CoT reasoning
- Complex & challenging tasks ### Plans:

- Train Llama 7b & 13b models
- Train Llama 70b QLoRA
- Generate V2 of the dataset, with more categories and GPT-4 ### How does it work?

1. Generate list of categories, prompts, sysprompts, etc (human)
2. Generate seed prompts (GPT)
3. Evolve prompts (GPT)
4. Generate responses (GPT)
5. Convert to Alpaca dataset format

Included in this repo is the script to generate the dataset.  However, it is buggy and probably not the best implementation possible.
passage: TAGS
#license-mit #region-us 
# EverythingLM Dataset

EverythingLM is a diverse instruct dataset consisting of ~1k sets of system prompts, instructions, and corresponding responses. These sets were generated using principles from both evol-instruct and Orca. The dataset encompasses a wide array of topics and interactions.### Categories:

- Reasoning
- Creative Writing
- General Knowledge
- Brainstorming
- Search Query
- Coding
- Basic Instruct

We also leverage various system prompts for evol-instruct and for responding to prompts.
This dataset has also been filtered to remove OpenAI alignment.### How it stands out:

- Long, detailed outputs
- Humanlike creativity
- CoT reasoning
- Complex & challenging tasks### Plans:

- Train Llama 7b & 13b models
- Train Llama 70b QLoRA
- Generate V2 of the dataset, with more categories and GPT-4### How does it work?

1. Generate list of categories, prompts, sysprompts, etc (human)
2. Generate seed prompts (GPT)
3. Evolve prompts (GPT)
4. Generate responses (GPT)
5. Convert to Alpaca dataset format

Included in this repo is the script to generate the dataset.  However, it is buggy and probably not the best implementation possible.