How to use from
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
Quick Links

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

Downloads last month
45
GGUF
Model size
2B params
Architecture
qwen2
Hardware compatibility
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4-bit

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