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drwlf/MedraN-E4B-Uncensored-MLX-Quantized
MedraN-E4B-Uncensored-MLX-Quantized is a machine learning model from drwlf. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for mlx. The card lists the license as other.
This repository contains quantized MLX-optimized versions of nicoboss/MedraN-E4B-Uncensored-EP7, converted for use with Apple Silicon devices using the MLX framework.
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Updated Sep 26, 2025
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From the Hugging Face model README
This repository contains quantized MLX-optimized versions of nicoboss/MedraN-E4B-Uncensored-EP7, converted for use with Apple Silicon devices using the MLX framework.
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.
This repository includes two quantized versions optimized for different use cases:
These models are optimized for use with the MLX framework on Apple Silicon devices. You can use them with:
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)
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)
| Version | Size | Quality | Speed | Memory Usage |
|---|---|---|---|---|
| Q6 | 5.2GB | High | Good | Medium |
| Q4 | 3.6GB | Good | Fast | Low |
| Full | 13GB | Best | Slow | High |
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
This model follows the same licensing terms as the original model. Please refer to the original model's license for usage terms.