Instructions to use Elkheta/elkheta-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Elkheta/elkheta-model with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf Elkheta/elkheta-model:Q4_K_M # Run inference directly in the terminal: llama cli -hf Elkheta/elkheta-model:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Elkheta/elkheta-model:Q4_K_M # Run inference directly in the terminal: llama cli -hf Elkheta/elkheta-model:Q4_K_M
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 Elkheta/elkheta-model:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Elkheta/elkheta-model:Q4_K_M
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 Elkheta/elkheta-model:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Elkheta/elkheta-model:Q4_K_M
Use Docker
docker model run hf.co/Elkheta/elkheta-model:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Elkheta/elkheta-model with Ollama:
ollama run hf.co/Elkheta/elkheta-model:Q4_K_M
- Unsloth Studio
How to use Elkheta/elkheta-model 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 Elkheta/elkheta-model 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 Elkheta/elkheta-model to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Elkheta/elkheta-model to start chatting
- Docker Model Runner
How to use Elkheta/elkheta-model with Docker Model Runner:
docker model run hf.co/Elkheta/elkheta-model:Q4_K_M
- Lemonade
How to use Elkheta/elkheta-model with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Elkheta/elkheta-model:Q4_K_M
Run and chat with the model
lemonade run user.elkheta-model-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Upload README.md with huggingface_hub
Browse files
README.md
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This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
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- For text only LLMs: `llama-cli -hf aliaaokilyy/elkheta-model --jinja`
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- For multimodal models: `llama-mtmd-cli -hf aliaaokilyy/elkheta-model --jinja`
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##
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##
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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license: apache-2.0
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base_model: unsloth/Qwen2-7B-Instruct-bnb-4bit
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tags:
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- geography
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- education
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- arabic
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- egyptian-dialect
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# Elkheta Model - Geography Assistant
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هذا الموديل هو مساعد تعليمي متخصص في مادة الجغرافيا لطلاب الثانوية العامة في مصر.
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## تفاصيل الموديل:
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- **Architecture:** Qwen2-7B (Fine-tuned using Unsloth)
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- **Task:** Answering geography questions in Egyptian Arabic dialect.
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- **Dataset:** 970 high-quality geography examples.
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## طريقة الاستخدام:
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تم تدريب الموديل باستخدام تنسيق معين (Prompt Style):
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`أنت مساعد تعليمي ودود وحماسي لمادة جغرافيا لطالب واحد في Senior 3.`
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