Serve a .tic
Load a compressed .tic bundle and run OpenAI-compatible inference.
Port 8000 by default. Model output is unchanged: no quantization, no approximation.
Usage
isiro serve <bundle> --target vllm [--host HOST] [--port PORT]<bundle>: a compiled -TIC folder or path to model.tic inside it. Config and tokenizer files sit beside the .tic. The same path form works for isiro verify and isiro info.
--target: required; vllm in v0.1.0.
--host / --port: override serve.yaml when passed. Prometheus /metrics is on the same port.
Serve settings
The TIC bundle includes serve.yaml. You can edit it for defaults such as host, port, max_model_len, gpu_memory_utilization, and the target image tag under targets.vllm. More target options can go there too.
CLI --host and --port override the file when you pass them. For tested image tags, run isiro status --compat. For flag details, run isiro serve --help.
The bundle must already be on the machine.
An example TIC bundle can be downloaded from Hugging Face e.g.
# Install Hugging Face Hub
python -m venv .venv
source .venv/bin/activate
pip install --upgrade huggingface_hub
# Download
hf download isiroai/Qwen2.5-7B-Instruct-TIC --local-dir Qwen2.5-7B-Instruct-TIC(Linux / macOS sample. More install options: Hugging Face installation)
isiro serve Qwen2.5-7B-Instruct-TIC --target vllmStop
docker stop isiro-serve-8000Use the port you passed (default 8000). Container name is isiro-serve-<port>.
Ctrl+C in the serve terminal may leave the container holding the GPU or port; if that happens, run the same docker stop command.
NVIDIA GPU supported today.
Run isiro serve --help for host, port, metrics, and other options.
See API for OpenAI-compatible endpoints. To chat from a browser UI, see Chat with your model.