Introduction of MedraN-E4B-Uncensored-MLX-Quantized
Model Details of 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)
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