Instructions to use Sal-Wwh/EriFix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Sal-Wwh/EriFix 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 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 serve -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 Desktop

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 serve -hf Sal-Wwh/EriFix:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/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

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

Hermes Agent

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 serve -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

Atomic Chat

OpenClaw

How to use Sal-Wwh/EriFix with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Sal-Wwh/EriFix:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "Sal-Wwh/EriFix:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Sal-Wwh commited on May 22

Commit

2faf04c

verified ·

1 Parent(s): 810241f

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	@@ -0,0 +1,118 @@

+---
+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