drwlf/MedraN-E4B-Uncensored-MLX-Quantized

Medra3n-E4B-Uncensored-MLX-Quantized

This repository contains quantized MLX-optimized versions of nicoboss/MedraN-E4B-Uncensored-EP7, converted for use with Apple Silicon devices using the MLX framework.

Model Description

MedraN (Medical Reasoning and Analysis) is a specialized language model fine-tuned for medical applications. This E4B (Episode 4B) variant is an uncensored version that provides comprehensive medical information without content restrictions.

Available Quantizations

This repository includes two quantized versions optimized for different use cases:

Q6 Version (6-bit quantization)

• Size: ~5.2GB
• Quality: High quality with minimal degradation
• Use case: Best balance between size and performance
• Actual quantization: 6.501 bits per weight

Q4 Version (4-bit quantization)

• Size: ~3.6GB
• Quality: Good quality with some degradation
• Use case: Maximum speed and memory efficiency
• Actual quantization: 4.501 bits per weight

Usage

These models are optimized for use with the MLX framework on Apple Silicon devices. You can use them with:

Q6 Version:

from mlx_lm import load, generate

model, tokenizer = load("drwlf/MedraN-E4B-Uncensored-MLX-Quantized", model_path="q6")
response = generate(model, tokenizer, "What are the symptoms of...", max_tokens=512)

Q4 Version:

from mlx_lm import load, generate

model, tokenizer = load("drwlf/MedraN-E4B-Uncensored-MLX-Quantized", model_path="q4")
response = generate(model, tokenizer, "What are the symptoms of...", max_tokens=512)

Model Comparison

Version	Size	Quality	Speed	Memory Usage
Q6	5.2GB	High	Good	Medium
Q4	3.6GB	Good	Fast	Low
Full	13GB	Best	Slow	High

Original Model

This is a conversion of the original model available at: https://huggingface.co/nicoboss/MedraN-E4B-Uncensored-EP7

Full precision MLX version: https://huggingface.co/drwlf/MedraN-E4B-Uncensored-MLX

Conversion Details

• Framework: MLX
• Base precision: float16
• Quantization: 4-bit and 6-bit
• Optimized for: Apple Silicon (M1/M2/M3/M4 chips)

License

This model follows the same licensing terms as the original model. Please refer to the original model's license for usage terms.