Mistral-7B-Instruct-v0.2-turkish-GGUF Open-Source Text Generation Model - Supports Bilingual Content Creation in Turkish and English

Mistral 7B Instruct V0.2 Turkish GGUF

Developed by sayhan

This is a Turkish text generation model fine-tuned based on Mistral-7B-Instruct-v0.2, supporting both Turkish and English.

Large Language Model Supports Multiple LanguagesOpen Source License:Apache-2.0 #Turkish instruction fine-tuning #Multilingual text generation #7B parameters

Downloads 336

Release Time : 2/9/2024

Model Overview

This model is the Turkish version of Mistral-7B-Instruct-v0.2, specifically fine-tuned for Turkish, suitable for text generation tasks.

Model Features

Turkish language support

Specially fine-tuned for Turkish, optimizing Turkish text generation capabilities.

Multilingual support

In addition to Turkish, it also supports English text generation.

Multiple quantization versions

Provides various quantization versions suitable for different hardware environments and performance needs.

Model Capabilities

Turkish text generation

English text generation

Instruction following

Use Cases

Natural Language Processing

Turkish chatbot

Can be used to build Turkish chatbots, providing natural and fluent conversational experiences.

Turkish content generation

Can be used to generate Turkish articles, stories, or other text content.

🚀 Mistral 7B Instruct v0.2 Turkish

This repository provides GGUF format model files for malhajar's Mistral 7B Instruct v0.2 Turkish, facilitating text generation in Turkish and English.

🚀 Quick Start

This README offers comprehensive details about the Mistral 7B Instruct v0.2 Turkish model, including its origin, quantization methods, and prompt template.

✨ Features

Multilingual Support: Supports both Turkish (tr) and English (en).
Text Generation: Ideal for text generation tasks.
Quantization Options: Offers various quantization methods to balance model size and quality.

📦 Installation

No specific installation steps are provided in the original document.

💻 Usage Examples

No code examples are provided in the original document.

📚 Documentation

Model Information

Property	Details
Base Model	malhajar/Mistral-7B-Instruct-v0.2-turkish
Language	tr, en
Pipeline Tag	text-generation
License	apache-2.0
Model Type	mistral
Library Name	transformers
Inference	false

Model Creators

Model creator: malhajar
Original model: Mistral-7B-Instruct-v0.2-turkish

Original Model Details

Developed by: Mohamad Alhajar
Language(s) (NLP): Turkish
Finetuned from model: mistralai/Mistral-7B-Instruct-v0.2

Quantization Methods

Quantization Method	Bits	Size	Use Case	Recommended
Q2_K	2	2.72 GB	Smallest, significant quality loss	❌
Q3_K_S	3	3.16 GB	Very small, high quality loss	❌
Q3_K_M	3	3.52 GB	Very small, high quality loss	❌
Q3_K_L	3	3.82 GB	Small, substantial quality loss	❌
Q4_0	4	4.11 GB	Legacy; small, very high quality loss	❌
Q4_K_S	4	4.14 GB	Small, greater quality loss	❌
Q4_K_M	4	4.37 GB	Medium, balanced quality	✅
Q5_0	5	5.00 GB	Legacy; medium, balanced quality	❌
Q5_K_S	5	5.00 GB	Large, low quality loss	✅
Q5_K_M	5	5.13 GB	Large, very low quality loss	✅
Q6_K	6	5.94 GB	Very large, extremely low quality loss	❌
Q8_0	8	7.70 GB	Very large, extremely low quality loss	❌
FP16	16	14.5 GB	Enormous, minuscule quality loss	❌

Prompt Template

### Instruction:
<prompt> (without the <>)
### Response:

🔧 Technical Details

The model is finetuned from the mistralai/Mistral-7B-Instruct-v0.2 model. Different quantization methods are available to adjust the model size according to specific requirements, with varying impacts on quality.

📄 License

This model is licensed under the apache-2.0 license.

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