---
library_name: transformers
datasets:
- ahmed000000000/cybersec
- dzakwan/cybersec
language:
- en
tags:
- conversational
---
# Model Card for Model ID

Works as a cyber assistant.



## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->

This is the model card of a 🤗 transformers model that has been pushed on the Hub.

- **Developed by:**  <a href="https://github.com/Zardian18">Zardian18</a>
- **Model type:** GPT2
- **Language(s) (NLP):** English
- **Finetuned from model [optional]:** <a href="https://huggingface.co/openai-community/gpt2-medium">OpenAi GPT2-medium</a>

### Model Sources [optional]

<!-- Provide the basic links for the model. -->

- **Repository:** <a href="https://github.com/Zardian18/CyberAssist">Github repo</a>

## Uses

Can be used to handle and solve basic cybersec queries.


## Bias, Risks, and Limitations

Currently it is fine-tuned on GPT2, which is good but not comparable to state of the art LLMs and Transformers. Moreover, the dataset is small.

[More Information Needed]


## How to Get Started with the Model

```# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Zardian/Cyber_assist3.0")

```
```# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Zardian/Cyber_assist3.0")
model = AutoModelForCausalLM.from_pretrained("Zardian/Cyber_assist3.0")

```

## Training Details

### Training Data

<a href="https://huggingface.co/datasets/ahmed000000000/cybersec">Cybersec queries and responses dataset</a> consisting of 12k enteries.

<a href="https://huggingface.co/datasets/dzakwan/cybersec">Cybersec dataset with instructions and output</a> consisting of 14k enteries.