Visionary-Llama is a flexible and extensible open-source platform designed to streamline a variety of AI-related tasks
Python
0
6 commits
updated Dec 2, 2024
Visionary-Llama is a flexible and extensible open-source platform designed to streamline a variety of AI-related tasks From summarization and question answering to image generation and refinement, this project provides an all-in-one interface for researchers, developers, and enthusiasts to explore and apply cutting-edge AI models.
. Multi-task Support: Includes functionalities such as text summarization, question answering, image generation, and more.
. Customizable Pipelines: Load and use different models (e.g., Stable Diffusion, Flux, Open LLMs) dynamically.
. GPU-Optimized: Leverages NVIDIA CUDA for enhanced performance.
. Extensible Design: Modular structure encourages adaptability and reusability.
. Community-Oriented: Fully open-source with opportunities for contribution.
.Summarization: Condense lengthy articles into concise summaries.
.Named Entity Recognition: Extract entities from text for NLP applications.
.Media Transcription: Convert audio/video files into text.
.Image Generation: Create and refine stunning visuals with advanced diffusion models and usage of LLMs as prompt enhancers.
.Image Refinement: Refine your image with your prompt with advanced diffusion model.
.Interactive Chat: Engage with large language models for creative and informative discussions.
Follow these steps to set up and deploy the application:
Prerequisites
Python 3.8+
NVIDIA GPU with CUDA 11.8 support (for GPU acceleration)
Docker (optional for containerized deployment)
Local Setup
Clone the Repository:
git clone https://github.com/Mhdaw/Visionary-Llama.git
cd Visionary-Llama
Install Dependencies:
pip install -r requirements.txt
Run the Application:
streamlit run app.py
Access the app in your browser at http://localhost:8501.
Docker Setup
Build the Docker Image:
docker build -t Visionary-Llama .
Run the Docker Container:
docker run --rm -p 8501:8501 --gpus all aVisionary-Llama
Access the app in your browser at http://localhost:8501.
Usage Instructions
Open the app in your browser.
Select a task from the tabs, such as "Summarization" or "Image Generation".
Follow the prompts to input data and execute the task.
View and download results as needed.
We welcome contributions to improve AI Task Assistant! Here’s how you can help:
Report Issues: Use the GitHub issues tracker to report bugs or request features.
Submit Pull Requests: Fork the repository, make changes, and submit a pull request.
Join Discussions: Engage with the community to share ideas and improvements.
For detailed contribution guidelines, refer to CONTRIBUTING.md (to be added).
This project is licensed under the MIT License. You’re free to use, modify, and distribute the code, but attribution is appreciated.
Join community for discussions:
GitHub Discussions
Start using Visionary-Llama today and simplify your AI workflows!
Visionary-Llama is a flexible and extensible open-source platform designed to streamline a variety of AI-related tasks
Python
0
6 commits
updated Dec 2, 2024
Visionary-Llama is a flexible and extensible open-source platform designed to streamline a variety of AI-related tasks From summarization and question answering to image generation and refinement, this project provides an all-in-one interface for researchers, developers, and enthusiasts to explore and apply cutting-edge AI models.
. Multi-task Support: Includes functionalities such as text summarization, question answering, image generation, and more.
. Customizable Pipelines: Load and use different models (e.g., Stable Diffusion, Flux, Open LLMs) dynamically.
. GPU-Optimized: Leverages NVIDIA CUDA for enhanced performance.
. Extensible Design: Modular structure encourages adaptability and reusability.
. Community-Oriented: Fully open-source with opportunities for contribution.
.Summarization: Condense lengthy articles into concise summaries.
.Named Entity Recognition: Extract entities from text for NLP applications.
.Media Transcription: Convert audio/video files into text.
.Image Generation: Create and refine stunning visuals with advanced diffusion models and usage of LLMs as prompt enhancers.
.Image Refinement: Refine your image with your prompt with advanced diffusion model.
.Interactive Chat: Engage with large language models for creative and informative discussions.
Follow these steps to set up and deploy the application:
Prerequisites
Python 3.8+
NVIDIA GPU with CUDA 11.8 support (for GPU acceleration)
Docker (optional for containerized deployment)
Local Setup
Clone the Repository:
git clone https://github.com/Mhdaw/Visionary-Llama.git
cd Visionary-Llama
Install Dependencies:
pip install -r requirements.txt
Run the Application:
streamlit run app.py
Access the app in your browser at http://localhost:8501.
Docker Setup
Build the Docker Image:
docker build -t Visionary-Llama .
Run the Docker Container:
docker run --rm -p 8501:8501 --gpus all aVisionary-Llama
Access the app in your browser at http://localhost:8501.
Usage Instructions
Open the app in your browser.
Select a task from the tabs, such as "Summarization" or "Image Generation".
Follow the prompts to input data and execute the task.
View and download results as needed.
We welcome contributions to improve AI Task Assistant! Here’s how you can help:
Report Issues: Use the GitHub issues tracker to report bugs or request features.
Submit Pull Requests: Fork the repository, make changes, and submit a pull request.
Join Discussions: Engage with the community to share ideas and improvements.
For detailed contribution guidelines, refer to CONTRIBUTING.md (to be added).
This project is licensed under the MIT License. You’re free to use, modify, and distribute the code, but attribution is appreciated.
Join community for discussions:
GitHub Discussions
Start using Visionary-Llama today and simplify your AI workflows!