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Install, compile to .tic, and serve. We currently support vLLM workloads on NVIDIA GPUs.

Compile to .tic

Compress model weights into lossless .tic files with the ISIRO compiler.

Weights stay bit-for-bit. Model output is unchanged: no quantization, no approximation. What is TIC?

Usage

isiro compile <input> [--model-id org/model] [-o path/] [-j N]

Supported inputs: a model directory or a single weight file (.safetensors, .onnx, .pth, .pt).

--model-id: Optional. Auto-filled from input metadata when available. Pass org/model (or the id your serve target expects) when compile asks for a model id.

-j / --jobs: Parallel packing workers (default 1). If you have enough memory, try -j 8 so multiple layers pack concurrently.

The input model must already be on the machine.

An example model 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 Qwen/Qwen2.5-7B-Instruct --local-dir Qwen2.5-7B-Instruct

(Linux / macOS sample. More install options: Hugging Face installation)

For gated models, run hf auth login first (create a token if needed).

isiro compile Qwen2.5-7B-Instruct --model-id Qwen/Qwen2.5-7B-Instruct -j 8

By default, compile writes a sibling -TIC folder (e.g. Qwen2.5-7B-Instruct-TIC/). Use -o / --output to set a custom bundle path.

Bundle layout

Qwen2.5-7B-Instruct-TIC/
  model.tic                  # packed weights
  model.tic.manifest.json    # hash manifest
  serve.yaml                 # defaults for isiro serve
  (sidecars)                 # config, tokenizer, and other files copied from input

Verify

Bit-exact checks. Hash manifest: model.tic.manifest.json.

# Confirm .tic integrity via the hash manifest
isiro verify Qwen2.5-7B-Instruct-TIC
 
# Optional: confirm .tic weights match the raw weights (requires compiler)
isiro verify Qwen2.5-7B-Instruct-TIC -r Qwen2.5-7B-Instruct

Run isiro compile --help for more options.

To serve, see Serve a .tic.