Small Thinker 3 B Preview abliterated i1 G G U F

Introduction

The SmallThinker-3B-Preview-abliterated-i1-GGUF is a quantized version of the SmallThinker-3B model, aimed at enhancing performance while maintaining a balance between size, speed, and quality. This model is uncensored and designed for conversational tasks, supporting English as its primary language.

Architecture

This model is based on the Transformers library and utilizes the GGUF format for quantization. The quantization process was handled by mradermacher, offering various weighted and imatrix quants, optimizing the model for both static and dynamic environments.

Training

The training process involves the application of weighted and imatrix quantization techniques to compress the original SmallThinker-3B model, maintaining functionality while reducing computational load. The quantization levels vary, and users can choose from several options based on their specific needs regarding size and performance.

Guide: Running Locally

To run the SmallThinker-3B-Preview-abliterated-i1-GGUF model locally:

1. Prerequisites: Ensure you have Python and the Transformers library installed.
2. Download the Model: Obtain the desired quantized model file from Hugging Face's repository.
3. Setup Environment: Create a virtual environment and install necessary dependencies.
4. Load the Model: Use the Transformers library to load the model into your environment.
5. Inference: Execute inference tasks with the model using your own datasets or inputs.

For optimal performance, especially with larger quant files, consider using cloud GPUs such as those provided by AWS, Google Cloud, or Azure.

License

The model and associated files are subject to Hugging Face's standard licensing terms. Users should review the license agreement on the Hugging Face platform to ensure compliance with usage restrictions and attributions.