Magnolia - Mell - v1 - 12B - GGUF Open-Source Text Generation Model, Free to Use! Achieve Efficient Content Creation

Magnolia Mell V1 12B GGUF

Developed by grimjim

A pre-trained language model fusion quantized GGUF file set created based on mergekit, using asymmetric gradient SLERP method to fuse two 12B parameter models, suitable for text generation tasks.

Large Language Model

Transformers

#SLERP fusion model #High-coherence text generation #Asymmetric gradient optimization

Downloads 182

Release Time : 5/31/2025

Model Overview

This is a 12B parameter language model fused via the SLERP method, focusing on narrative text generation with high coherence, ideal for creative writing and content generation.

Model Features

SLERP fusion technology

Uses spherical linear interpolation (SLERP) method for model fusion, balancing the characteristics of two source models

Temperature-sensitive generation

Can control the diversity and creativity of generated text by adjusting the temperature parameter (1.0-2.0)

High coherence

Demonstrates high coherence and logical consistency in narrative text completion tests

Model Capabilities

Text generation

Creative writing

Content continuation

Use Cases

Content creation

Story continuation

Continue a complete story based on a given beginning

Generates coherent and creative narrative content

Creative writing assistance

Helps writers overcome writer's block and provides content inspiration

Produces diverse writing suggestions and content snippets

🚀 Magnolia-Mell-v1-12B-GGUF

This project provides a set of quantized GGUF files for a merged pre - trained language model created using mergekit. It offers high - coherence narrative text completion, with some adjustable parameters to handle potential issues like repetition.

🚀 Quick Start

This is a set of quantized GGUF files for a merge of pre - trained language models created using mergekit.

An asymmetric gradient SLERP was used to lightly apply MN - 12B - Mag - Mell - R1 to Magnolia - v3 - 12B.

Tested for narrative text completion with temperature = 1.0 and minP = 0.02. Coherence is fairly high, though there may be occasional slips. If repetition is a problem, raising temperature briefly may help. The model appears to tolerate temperature = 2.0 even.

📚 Documentation

✨ Features

High - coherence Text Completion: Capable of generating narrative text with relatively high coherence.
Temperature Adjustability: Allows users to adjust the temperature parameter to deal with repetition issues.

📦 Installation

No specific installation steps are provided in the original README.

💻 Usage Examples

No code examples are provided in the original README.

🔧 Technical Details

Merge Details

Merge Method

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:

[inflatebot/MN - 12B - Mag - Mell - R1](https://huggingface.co/inflatebot/MN - 12B - Mag - Mell - R1)
[grimjim/Magnolia - v3 - 12B](https://huggingface.co/grimjim/Magnolia - v3 - 12B)

Configuration

The following YAML configuration was used to produce this model:

base_model: grimjim/Magnolia-v3-12B
dtype: bfloat16
merge_method: slerp
slices:
- sources:
  - model: grimjim/Magnolia-v3-12B
    layer_range: [0,40]
  - model: inflatebot/MN-12B-Mag-Mell-R1
    layer_range: [0,40]
parameters:
  t:
    - filter: self_attn
      value: [0.0,0.09]
    - filter: mlp
      value: [0.09,0.0]
    - value: [0.0,0.09]

📄 License

No license information is provided in the original README.

Property	Details
Base Model	grimjim/Magnolia - Mell - v1 - 12B
Library Name	transformers
Tags	mergekit, merge
Pipeline Tag	text - generation
Quantized By	grimjim

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