alexgusevski/Llama-3.3-8B-Instruct-128K_Abliterated-mlx-fp16
The alexgusevski/Llama-3.3-8B-Instruct-128K_Abliterated-mlx-fp16 model is an 8 billion parameter instruction-tuned language model, converted to the MLX format for efficient deployment. Based on the Llama-3.3 architecture, this model is designed for general instruction following tasks. Its primary differentiation lies in its MLX conversion, enabling optimized performance on Apple silicon.
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Model Overview
This model, alexgusevski/Llama-3.3-8B-Instruct-128K_Abliterated-mlx-fp16, is an 8 billion parameter instruction-tuned variant of the Llama-3.3 architecture. It has been specifically converted to the MLX format using mlx-lm version 0.29.1, originating from the SicariusSicariiStuff/Llama-3.3-8B-Instruct-128K_Abliterated base model. The _Abliterated designation typically implies further fine-tuning or modifications beyond the base Llama-3.3 model, though specific details are not provided in the source README.
Key Characteristics
- Architecture: Llama-3.3-8B-Instruct
- Parameter Count: 8 billion parameters
- Context Length: Supports a context window of 128K tokens (32768 tokens as per model info).
- Format: MLX-converted, optimized for Apple silicon.
- Instruction-tuned: Designed to follow user instructions effectively.
Use Cases
This model is suitable for developers looking to leverage an instruction-following LLM on Apple hardware. Its MLX conversion makes it ideal for:
- Local inference on devices with Apple silicon.
- General natural language understanding and generation tasks.
- Applications requiring a capable 8B parameter model with a large context window.