drwlf / MedraN-E4B-Uncensored-MLX-Quantized

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Model's Last Updated: September 26 2025

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)
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.

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More Information About MedraN-E4B-Uncensored-MLX-Quantized huggingface.co Model

More MedraN-E4B-Uncensored-MLX-Quantized license Visit here:

https://choosealicense.com/licenses/custom-license

MedraN-E4B-Uncensored-MLX-Quantized huggingface.co

MedraN-E4B-Uncensored-MLX-Quantized huggingface.co is an AI model on huggingface.co that provides MedraN-E4B-Uncensored-MLX-Quantized's model effect (), which can be used instantly with this drwlf MedraN-E4B-Uncensored-MLX-Quantized model. huggingface.co supports a free trial of the MedraN-E4B-Uncensored-MLX-Quantized model, and also provides paid use of the MedraN-E4B-Uncensored-MLX-Quantized. Support call MedraN-E4B-Uncensored-MLX-Quantized model through api, including Node.js, Python, http.

MedraN-E4B-Uncensored-MLX-Quantized huggingface.co Url

https://huggingface.co/drwlf/MedraN-E4B-Uncensored-MLX-Quantized

drwlf MedraN-E4B-Uncensored-MLX-Quantized online free

MedraN-E4B-Uncensored-MLX-Quantized huggingface.co is an online trial and call api platform, which integrates MedraN-E4B-Uncensored-MLX-Quantized's modeling effects, including api services, and provides a free online trial of MedraN-E4B-Uncensored-MLX-Quantized, you can try MedraN-E4B-Uncensored-MLX-Quantized online for free by clicking the link below.

drwlf MedraN-E4B-Uncensored-MLX-Quantized online free url in huggingface.co:

https://huggingface.co/drwlf/MedraN-E4B-Uncensored-MLX-Quantized

MedraN-E4B-Uncensored-MLX-Quantized install

MedraN-E4B-Uncensored-MLX-Quantized is an open source model from GitHub that offers a free installation service, and any user can find MedraN-E4B-Uncensored-MLX-Quantized on GitHub to install. At the same time, huggingface.co provides the effect of MedraN-E4B-Uncensored-MLX-Quantized install, users can directly use MedraN-E4B-Uncensored-MLX-Quantized installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

MedraN-E4B-Uncensored-MLX-Quantized install url in huggingface.co:

https://huggingface.co/drwlf/MedraN-E4B-Uncensored-MLX-Quantized

Url of MedraN-E4B-Uncensored-MLX-Quantized

MedraN-E4B-Uncensored-MLX-Quantized huggingface.co Url

Provider of MedraN-E4B-Uncensored-MLX-Quantized huggingface.co

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