Instructions to use GakoMammang/nurse-ai-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GakoMammang/nurse-ai-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="GakoMammang/nurse-ai-model", device_map="auto")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("GakoMammang/nurse-ai-model", dtype="auto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use GakoMammang/nurse-ai-model with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "GakoMammang/nurse-ai-model" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GakoMammang/nurse-ai-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/GakoMammang/nurse-ai-model
- SGLang
How to use GakoMammang/nurse-ai-model with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "GakoMammang/nurse-ai-model" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GakoMammang/nurse-ai-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "GakoMammang/nurse-ai-model" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GakoMammang/nurse-ai-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use GakoMammang/nurse-ai-model with Docker Model Runner:
docker model run hf.co/GakoMammang/nurse-ai-model
Mobile-Optimized Inference Engine
This repository contains a quantized version of the Google Gemma model, specifically formatted for on-device inference in mobile applications.
π οΈ Technical Details
- Architecture: Gemma-2B / Gemma-3 (Quantized)
- Format: .bin / .task
- Target: Mobile NPU/GPU Acceleration (MediaPipe/LiteRT)
π Privacy & Data Security
This asset is intended for Local-First applications.
- All data processing occurs on the local device hardware.
- No data is transmitted to external servers during inference.
- Ideal for high-security environments requiring strict data-in-transit protocols.
π License & Terms
This model is distributed under the Gemma Terms of Use. By using this asset, you acknowledge and agree to the Google Prohibited Use Policy.
π Usage
This engine is designed to assist with text-based tasks including summarization, professional formatting, and logic auditing. It is optimized for efficiency on devices with constrained RAM and battery life.
Disclaimer: This is a documentation and logic assistant. It is not intended to provide professional, legal, or medical advice. The end-user remains the sole authority for any output generated.
Version: 1.2.0