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