Lamarck 14 B v0.6 rc4 i1 G G U F

Introduction

The Lamarck-14B-v0.6-rc4-i1-GGUF model is a quantized version of the base model Lamarck-14B-v0.6, optimized for various use cases. It is designed to support efficient inference and deployment using the GGUF framework. This model is part of the Hugging Face ecosystem, leveraging the transformers library.

Architecture

The model utilizes the GGUF quantization framework, which includes weighted/imatrix quants, aimed at enhancing performance and efficiency. Various quantization types and sizes are available, providing flexibility in choosing the appropriate balance between model size and quality.

Training

The model was quantized by mradermacher using the base model from sometimesanotion. The quantization process involves converting the original model into GGUF files, which are optimized for deployment and inference. The process allows for handling large language models (LLMs) with reduced resource requirements.

Guide: Running Locally

To run the model locally, follow these steps:

1. Setup Environment: Ensure you have Python and the Hugging Face transformers library installed.
2. Download Model Files: Access the GGUF model files from the Hugging Face repository.
3. Load Model: Use the transformers library to load the GGUF model for inference.
4. Inference: Execute inference tasks as required by your application.

For improved performance, consider using cloud GPUs such as those offered by AWS, Google Cloud, or Azure, which provide scalable resources for handling large models efficiently.

License

The model is released under the Apache-2.0 license, allowing for broad use, distribution, and modification, while maintaining the requirement for attribution and inclusion of the license in derivative works.