Saba1.5 Pro G G U F

Introduction

The Saba1.5-Pro-GGUF model is a quantized version of the base model Sakalti/Saba1.5-Pro, developed by mradermacher. It leverages the GGUF library for efficient inference and is designed for conversational and inference endpoint applications. The model is available under the Apache 2.0 license.

Architecture

The model is based on transformers and is quantized using GGUF by mradermacher. It supports various quantization levels to optimize performance and quality, with options ranging from Q2_K to f16.

Training

The model was trained using the HuggingFaceH4/ultrachat_200k dataset. The quantization process involved creating static and weighted/imatrix quant versions to suit different use cases and resource availability.

Guide: Running Locally

1. Set Up Environment: Ensure you have Python and the necessary libraries installed. Use pip install transformers to get the Transformers library.
2. Download Model: Choose the desired quantized version from the provided links, such as Q3_K_S or Q8_0, based on your quality and performance needs.
3. Load Model: Utilize the Transformers library to load the model in your script.
4. Run Inference: Use the model for your specific application, such as conversational agents or other NLP tasks.

For optimal performance, especially with larger models, consider using cloud GPUs from providers such as AWS, Google Cloud Platform, or Azure.

License

The Saba1.5-Pro-GGUF model is released under the Apache 2.0 license, permitting use, distribution, and modification, provided that proper attribution is given.