Deep Seek V3 3bit bf16

Introduction

The MLX-COMMUNITY/DEEPSEEK-V3-3BIT-BF16 is a model converted to the MLX format from the original deepseek-ai/DeepSeek-V3 model. This conversion utilizes the mlx-lm version 0.20.4, allowing for efficient model loading and inference.

Architecture

This model is based on the DeepSeek-V3 architecture, optimized for performance using a 3-bit precision format with bf16 (bfloat16) data types. The architecture is designed to enable efficient computation while maintaining high accuracy.

Training

The model was initially trained under the deepseek-ai/DeepSeek-V3 project. The conversion to MLX format facilitates its use in applications requiring reduced memory footprint and computational resources without significant loss in performance.

Guide: Running Locally

1. Install MLX-LM: Ensure you have the required library by running:

   pip install mlx-lm
   

2. Load the Model:

   from mlx_lm import load, generate
   
   model, tokenizer = load("mlx-community/DeepSeek-V3-3bit-bf16")
   

3. Generate a Response:

   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)
   

4. Cloud GPUs: For enhanced performance, especially with large-scale data or intensive tasks, consider using cloud GPUs from platforms like AWS, Google Cloud, or Azure.

License

The license details for this model can be found on the Hugging Face model page. Ensure compliance with any usage restrictions or guidelines provided by the original model creators.