Text Generation
GGUF
English
Tigrinya
qwen
offline-ai
troubleshooting
android
unsloth
qlora
tigrinya
eritrea
conversational
Instructions to use Sal-Wwh/EriFix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Sal-Wwh/EriFix with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Sal-Wwh/EriFix", filename="EriFix_Merged_Model.Q4_K_M.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Sal-Wwh/EriFix with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Sal-Wwh/EriFix:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Sal-Wwh/EriFix:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Sal-Wwh/EriFix:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Sal-Wwh/EriFix: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 Sal-Wwh/EriFix:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Sal-Wwh/EriFix: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 Sal-Wwh/EriFix:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Sal-Wwh/EriFix:Q4_K_M
Use Docker
docker model run hf.co/Sal-Wwh/EriFix:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use Sal-Wwh/EriFix with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Sal-Wwh/EriFix" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Sal-Wwh/EriFix", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Sal-Wwh/EriFix:Q4_K_M
- Ollama
How to use Sal-Wwh/EriFix with Ollama:
ollama run hf.co/Sal-Wwh/EriFix:Q4_K_M
- Unsloth Studio
How to use Sal-Wwh/EriFix 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 Sal-Wwh/EriFix 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 Sal-Wwh/EriFix to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Sal-Wwh/EriFix to start chatting
- Pi
How to use Sal-Wwh/EriFix with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Sal-Wwh/EriFix:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "Sal-Wwh/EriFix:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Sal-Wwh/EriFix with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Sal-Wwh/EriFix:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default Sal-Wwh/EriFix:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use Sal-Wwh/EriFix with Docker Model Runner:
docker model run hf.co/Sal-Wwh/EriFix:Q4_K_M
- Lemonade
How to use Sal-Wwh/EriFix with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Sal-Wwh/EriFix:Q4_K_M
Run and chat with the model
lemonade run user.EriFix-Q4_K_M
List all available models
lemonade list
| license: apache-2.0 | |
| language: | |
| - en | |
| - ti | |
| tags: | |
| - qwen | |
| - gguf | |
| - offline-ai | |
| - troubleshooting | |
| - android | |
| - unsloth | |
| - qlora | |
| - tigrinya | |
| - eritrea | |
| pipeline_tag: text-generation | |
| # EriFix AI | |
| EriFix AI is an offline troubleshooting and maintenance and Teaching assistant | |
| fine-tuned for Eritrean and general technology support. | |
| The model is optimized for: | |
| - Android offline AI | |
| - smartphone troubleshooting | |
| - laptop and desktop support | |
| - Windows troubleshooting | |
| - router and networking problems | |
| - solar and inverter troubleshooting | |
| - printer/copier/scanner support | |
| - DIY repair guidance | |
| - maintenance assistance | |
| --- | |
| # Base Model | |
| Qwen/Qwen2.5-1.5B-Instruct | |
| --- | |
| # Training Method | |
| - QLoRA fine-tuning | |
| - Unsloth optimization | |
| - 4-bit training | |
| - GGUF export | |
| - Quantization: Q4_K_M | |
| --- | |
| # Supported Languages | |
| - English | |
| - Tigrinya | |
| - Mixed English + Tigrinya | |
| --- | |
| # Optimized For | |
| - Android phones | |
| - Offline AI assistants | |
| - llama.cpp | |
| - MLC Chat | |
| - PocketPal AI | |
| --- | |
| # Recommended RAM | |
| Minimum: | |
| - 4GB RAM | |
| Recommended: | |
| - 6GB+ RAM | |
| --- | |
| # Intended Use | |
| EriFix AI is designed for: | |
| - troubleshooting guidance | |
| - maintenance support | |
| - educational technology assistance | |
| - offline technical support | |
| - Offline Technological Assistance | |
| --- | |
| # Limitations | |
| EriFix AI may: | |
| - generate incorrect troubleshooting steps | |
| - hallucinate technical information | |
| - provide incomplete repair guidance | |
| Because of Low Data all the above mentioned may or may not happen. | |
| Always verify critical repairs and electrical work carefully. | |
| --- | |
| # Developer | |
| Developed by: | |
| Saleh Omer | |
| @Sal-Wwh | |
| salehomer200202@gmail.com | |
| +2917594507 | |
| Project: | |
| EriFix AI | |
| Country: | |
| Eritrea | |