Deep Seek V3 3bit

Introduction

The mlx-community/DeepSeek-V3-3bit model is a conversion of deepseek-ai/DeepSeek-V3 into the MLX format. This model is designed for efficient processing using 3-bit precision, facilitating reduced computational requirements while maintaining performance.

Architecture

The model utilizes the MLX library, which allows for the handling of models with precision-reduced formats like 3-bit. This architecture is based on the underlying capabilities of deepseek-ai/DeepSeek-V3 and leverages the MLX framework to optimize for size and speed.

Training

The original DeepSeek-V3 model was trained using high-quality datasets to achieve robust performance. The conversion to a 3-bit model in MLX format ensures that these performance characteristics are maintained while optimizing for lower resource utilization.

Guide: Running Locally

To run DeepSeek-V3-3bit locally, follow these steps:

1. Install the MLX library:

   pip install mlx-lm
   

2. Load the model and generate a response:

   from mlx_lm import load, generate
   
   model, tokenizer = load("mlx-community/DeepSeek-V3-3bit")
   
   prompt = "hello"
   
   if tokenizer.chat_template is not None:
       messages = [{"role": "user", "content": prompt}]
       prompt = tokenizer.apply_chat_template(messages, add_generation_prompt=True)
   
   response = generate(model, tokenizer, prompt=prompt, verbose=True)
   

3. Hardware Recommendations:
   For optimal performance, consider using cloud GPUs such as those provided by AWS, Google Cloud, or Azure. These platforms offer scalable resources suitable for handling models like DeepSeek-V3-3bit.

License

The usage of mlx-community/DeepSeek-V3-3bit is governed by the licensing agreements specified by its original author. Ensure compliance with all legal terms before deploying the model in production environments.