Text Generation
Transformers
English
Spanish
iot
smart-home
home-assistant
tool-calling
agent
cybersecurity
devops
ollama
inference-pipeline
autonomous-agent
raspberry-pi
qwen3-coder
Instructions to use MrMoz33/tokioai-coder-iot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MrMoz33/tokioai-coder-iot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="MrMoz33/tokioai-coder-iot")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MrMoz33/tokioai-coder-iot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use MrMoz33/tokioai-coder-iot with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "MrMoz33/tokioai-coder-iot" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MrMoz33/tokioai-coder-iot", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/MrMoz33/tokioai-coder-iot
- SGLang
How to use MrMoz33/tokioai-coder-iot 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 "MrMoz33/tokioai-coder-iot" \ --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": "MrMoz33/tokioai-coder-iot", "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 "MrMoz33/tokioai-coder-iot" \ --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": "MrMoz33/tokioai-coder-iot", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use MrMoz33/tokioai-coder-iot with Docker Model Runner:
docker model run hf.co/MrMoz33/tokioai-coder-iot
Download pyproject.toml from MrMoz33/tokioai-coder-iot: direct link, hf CLI and curl.
- Browser
- Download file 580 Bytes
-
https://huggingface.co/MrMoz33/tokioai-coder-iot/resolve/main/pyproject.toml
- Command line
-
hf download hf://MrMoz33/tokioai-coder-iot/pyproject.toml
-
curl -L -o pyproject.toml https://huggingface.co/MrMoz33/tokioai-coder-iot/resolve/main/pyproject.toml
580 Bytes
| [build-system] | |
| requires = ["setuptools>=45", "wheel"] | |
| build-backend = "setuptools.build_meta" | |
| [project] | |
| name = "tokioai-engine" | |
| version = "1.0.0" | |
| description = "Transform any small open model into an elite AI agent" | |
| readme = "README.md" | |
| license = {text = "MIT"} | |
| requires-python = ">=3.8" | |
| authors = [{name = "TokioAI"}] | |
| keywords = ["ai", "llm", "inference", "tool-calling", "agent", "security", "ollama"] | |
| dependencies = ["requests>=2.28", "flask>=2.0"] | |
| [project.scripts] | |
| tokioai-engine = "engine.server:main" | |
| [project.optional-dependencies] | |
| dev = ["pytest>=7.0", "openai>=1.0"] | |