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---
license: apache-2.0
tags:
- unsloth
- trl
- sft
---
# DogeGPT Meme Coin 🐕🤖
The Meme Coin will be launched Soon
Join our socials to find out more (and invest early🐕)
All other DogeGPTs are all fake, only check the following socials for update
Share them and mention us on X(twitter)
<p align="center">
<!-- Twitter Icon -->
<a href="https://x.com/doge_gpt1" target="_blank">
<img src="https://img.shields.io/badge/Twitter-1DA1F2?style=for-the-badge&logo=twitter&logoColor=white" alt="Follow on Twitter">
</a>
<!-- YouTube Icon -->
<a href="https://www.youtube.com/@dogegpt" target="_blank">
<img src="https://img.shields.io/badge/YouTube-FF0000?style=for-the-badge&logo=youtube&logoColor=white" alt="Subscribe on YouTube">
</a>
<!-- Website Icon -->
<a href="https://dogegpt.org/" target="_blank">
<img src="https://img.shields.io/badge/Website-0A66C2?style=for-the-badge&logo=google-chrome&logoColor=white" alt="Visit Our Website">
</a>
</p>
# DogeGPT1-1B 🐕🤖
DogeGPT1-1B is an open-sourced **1.24B-parameter Large Language Model (LLM)** designed to bring the fun of meme coins and the power of AI together! Built on the **LLaMA architecture**, DogeGPT is tailored for conversational AI applications with a playful twist. Whether you're a meme coin enthusiast, developer, or AI explorer, DogeGPT is here to spark your creativity.
**3B and 8B -parameter LLMs will be annonced soon**
---
## Model Overview 🚀
- **Model Name**: DogeGPT1-1B
- **Architecture**: LLaMA
- **Model Size**: 1.24B parameters
- **Quantization Formats**: GGUF (2-bit, 3-bit, 4-bit, 5-bit, 6-bit, 8-bit)
- **License**: Apache 2.0
- **Tags**: `PyTorch`, `LLaMA`, `TRL`, `GGUF`, `conversational`
- **Downloads Last Month**: 115
---
## Features 🌟
- **Conversational AI**: Perfect for building chatbots, virtual assistants, or meme-themed conversational models.
- **Quantization Support**: Includes efficient formats for deployment in resource-constrained environments.
- **Open Source**: Fully available under the permissive Apache 2.0 license.
---
## Getting Started 🛠️
### Installation
Clone the model and install the necessary dependencies:
```bash
pip install transformers huggingface_hub
```
### Usage Example
Here’s how to load DogeGPT1-1B using transformers:
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
# Load the model and tokenizer
model = AutoModelForCausalLM.from_pretrained("Doge-GPT/DogeGPT1-1B")
tokenizer = AutoTokenizer.from_pretrained("Doge-GPT/DogeGPT1-1B")
# Generate text
input_text = "What is DogeGPT?"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=50)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```
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