Instructions to use Ellbendls/Qwen-2.5-3b-Quran-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Ellbendls/Qwen-2.5-3b-Quran-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Ellbendls/Qwen-2.5-3b-Quran-GGUF", dtype="auto")

llama-cpp-python

How to use Ellbendls/Qwen-2.5-3b-Quran-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Ellbendls/Qwen-2.5-3b-Quran-GGUF",
	filename="Qwen-2.5-3b-Quran.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Ellbendls/Qwen-2.5-3b-Quran-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Ellbendls/Qwen-2.5-3b-Quran-GGUF
# Run inference directly in the terminal:
llama-cli -hf Ellbendls/Qwen-2.5-3b-Quran-GGUF

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Ellbendls/Qwen-2.5-3b-Quran-GGUF
# Run inference directly in the terminal:
llama-cli -hf Ellbendls/Qwen-2.5-3b-Quran-GGUF

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf Ellbendls/Qwen-2.5-3b-Quran-GGUF
# Run inference directly in the terminal:
./llama-cli -hf Ellbendls/Qwen-2.5-3b-Quran-GGUF

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf Ellbendls/Qwen-2.5-3b-Quran-GGUF
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Ellbendls/Qwen-2.5-3b-Quran-GGUF

Use Docker

docker model run hf.co/Ellbendls/Qwen-2.5-3b-Quran-GGUF

LM Studio
Jan
Ollama
How to use Ellbendls/Qwen-2.5-3b-Quran-GGUF with Ollama:
```
ollama run hf.co/Ellbendls/Qwen-2.5-3b-Quran-GGUF
```

Unsloth Studio

How to use Ellbendls/Qwen-2.5-3b-Quran-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Ellbendls/Qwen-2.5-3b-Quran-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Ellbendls/Qwen-2.5-3b-Quran-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Ellbendls/Qwen-2.5-3b-Quran-GGUF to start chatting

Docker Model Runner
How to use Ellbendls/Qwen-2.5-3b-Quran-GGUF with Docker Model Runner:
```
docker model run hf.co/Ellbendls/Qwen-2.5-3b-Quran-GGUF
```

Lemonade

How to use Ellbendls/Qwen-2.5-3b-Quran-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Ellbendls/Qwen-2.5-3b-Quran-GGUF

Run and chat with the model

lemonade run user.Qwen-2.5-3b-Quran-GGUF-{{QUANT_TAG}}

List all available models

lemonade list

Model Card for Fine-Tuned Qwen2.5-3B-Instruct

This is a fine-tuned version of the Qwen2.5-3B-Instruct model. The fine-tuning process utilized the Quran Indonesia Tafseer Translation dataset, which provides translations and tafsir in Bahasa Indonesia for the Quran.

Model Details

Model Description

Base Model: Qwen2.5-3B-Instruct
Fine-Tuned By: Ellbendl Satria
Dataset: emhaihsan/quran-indonesia-tafseer-translation
Language: Bahasa Indonesia
License: MIT

This model is designed for NLP tasks involving Quranic text in Bahasa Indonesia, including understanding translations and tafsir.

Uses

Direct Use

This model can be used for applications requiring the understanding, summarization, or retrieval of Quranic translations and tafsir in Bahasa Indonesia.

Downstream Use

It is suitable for fine-tuning on tasks such as:

Quranic text summarization
Question answering systems related to Islamic knowledge
Educational tools for learning Quranic content in Indonesian

Biases

The model inherits any biases present in the dataset, which is specific to Islamic translations and tafsir in Bahasa Indonesia.

Recommendations

Users should ensure that applications using this model respect cultural and religious sensitivities.
Results should be verified by domain experts for critical applications.

Downloads last month: 11

GGUF

Model size

3B params

Architecture

qwen2

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

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Model tree for Ellbendls/Qwen-2.5-3b-Quran-GGUF

Base model

Qwen/Qwen2.5-3B

Finetuned

Qwen/Qwen2.5-3B-Instruct

Quantized

(231)

this model

Ellbendls
/

Qwen-2.5-3b-Quran-GGUF