sigclip_vision_patch14_384

Introduction

The sigclip_vision_patch14_384 model is a project hosted on the Hugging Face platform, developed by the user funnewsr. This model is accessible for public use and is primarily designed for visual processing tasks.

Architecture

Details about the specific architecture of sigclip_vision_patch14_384 are not provided in the available documentation. Generally, models with similar naming conventions often indicate a Vision Transformer (ViT) architecture with a patch size of 14x14 and an input resolution of 384x384 pixels.

Training

The training specifics for this model, such as datasets used, hyperparameters, and training duration, have not been disclosed in the provided README. Typically, similar models are trained on large-scale image datasets using advanced optimization techniques.

Guide: Running Locally

To run the sigclip_vision_patch14_384 model locally, follow these basic steps:

1. Clone the Repository:

   git clone https://huggingface.co/funnewsr/sigclip_vision_patch14_384
   

2. Install Required Libraries: Ensure you have Python and necessary libraries installed, such as transformers and torch.

   pip install transformers torch
   

3. Run the Model: Load and run the model using a script or an interactive Python session.

4. Use Cloud GPUs: For performance improvements, consider using cloud-based GPU services such as AWS, Google Cloud, or Azure.

License

The sigclip_vision_patch14_384 model is licensed under the Apache 2.0 License. This allows for a high degree of freedom in using, modifying, and distributing the model, provided that any modifications are also shared under the same license.