Switti 1024

Introduction

Switti-1024 is a machine learning model developed by Yandex Research and hosted on Hugging Face. It utilizes the PyTorchModelHubMixin for seamless integration with the Hugging Face Hub, facilitating easy model sharing and deployment.

Architecture

Switti-1024 is built using PyTorch, leveraging the PyTorchModelHubMixin for integration. This mixin provides utilities for model uploading and version control within the Hugging Face ecosystem. The specific architecture details and model parameters are not provided in the available documentation.

Training

The training specifics, including datasets, epochs, and computational resources used, are not detailed in the available documentation. For comprehensive training details, additional information from the developers may be required.

Guide: Running Locally

To run Switti-1024 locally:

1. Clone the Repository: Use Git to clone the Switti-1024 repository from Hugging Face.

   git clone https://huggingface.co/yresearch/Switti-1024
   

2. Set Up Environment: Ensure you have Python and PyTorch installed. Create a virtual environment and install necessary dependencies.

   python -m venv env
   source env/bin/activate
   pip install -r requirements.txt
   

3. Load the Model: Use PyTorch to load the model.

   from transformers import AutoModel
   model = AutoModel.from_pretrained("yresearch/Switti-1024")
   

4. Run Inference: Implement inference code to use the model for predictions.

For optimal performance, it is recommended to use cloud GPUs from providers like AWS, Google Cloud, or Azure to handle the computational load efficiently.

License

The licensing information for Switti-1024 is not specified in the provided documentation. Users should consult the Hugging Face model card or contact the developers for clarification on usage rights and restrictions.