tensor-man
is a utility to inspect, validate, sign and verify machine learning model files.
Important
PyTorch models are loaded and inspected in a networkless Docker container in order to prevent unintended code execution on the host machine.
This is the recommended way to install and use the tool:
cargo install tensor-man
docker pull dreadnode/tensor-man:latest
To build your own Docker image for the tool, run:
docker build . -t tman
If you want to inspect PyTorch models and you are using tensor-man
inside a container, make sure to share the docker socket from the host machine with the container:
docker run -it \
# these paths must match
-v/path/to/pytorch_model.bin:/path/to/pytorch_model.bin \
# allow the container itself to instrument docker on the host
-v/var/run/docker.sock:/var/run/docker.sock \
# the rest of the command line
tman inspect /path/to/pytorch_model.bin
Alternatively you can build the project from source, in which case you'll need to have Rust and Cargo installed on your system.
Once you have those set up, clone the repository and build the project:
cargo build --release
The compiled binary will be available in the target/release
directory. You can run it directly or add it to your system's PATH:
# Run directly
./target/release/tman
# Or, copy to a directory in your PATH (e.g., /usr/local/bin)
sudo cp target/release/tman /usr/local/bin/
Inspect a file and print a brief summary:
tman inspect /path/to/whatever/llama-3.1-8b-instruct.safetensors
Print detailed information about each tensor:
tman inspect /path/to/whatever/llama-3.1-8b-instruct.safetensors --detail full
Filter by tensor name:
tman inspect /path/to/whatever/llama-3.1-8b-instruct.onnx -D full --filter "q_proj"
Save the output as JSON:
tman inspect /path/to/whatever/llama-3.1-8b-instruct.gguf -D full --to-json output.json
The tool allows you to generate an Ed25519 key pair to sign your models:
tman create-key --private-key private.key --public-key public.key
Then you can use the private key to sign a model (this will automatically include and sign external data files if referenced by the format):
# this will generate the tinyyolov2-8.signature file
tman sign /path/to/whatever/tinyyolov2-8.onnx -K /path/to/private.key
# you can provide a safetensors index file and all files referenced by it will be signed as well
tman sign /path/to/whatever/Meta-Llama-3-8B/model.safetensors.index.json -K /path/to/private.key
# this will sign the entire model folder with every file in it
tman sign /path/to/whatever/Meta-Llama-3-8B/ -K /path/to/private.key
And the public one to verify the signature:
# will verify the signature in tinyyolov2-8.signature
tman verify /path/to/whatever/tinyyolov2-8.onnx -K /path/to/public.key
# will verify with an alternative signature file
tman verify /path/to/whatever/tinyyolov2-8.onnx -K /path/to/public.key --signature /path/to/your.signature
# this will verify every file in the model folder
tman sign /path/to/whatever/Meta-Llama-3-8B/ -K /path/to/public.key
Generate a .dot file for the execution graph of an ONNX model:
tman graph /path/to/whatever/tinyyolov2-8.onnx --output tinyyolov2-8.dot
For the full list of commands and options, run:
tman --help
# get command specific help
tman inspect --help
This tool is released under the GPL 3 license. To see the licenses of the project dependencies, install cargo license with cargo install cargo-license
and then run cargo license
.