https://github.com/dreadnode/tensor-man
A utility to inspect, validate, sign and verify machine learning model files.
https://github.com/dreadnode/tensor-man
gguf onnx pytorch safetensors
Last synced: 2 months ago
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A utility to inspect, validate, sign and verify machine learning model files.
- Host: GitHub
- URL: https://github.com/dreadnode/tensor-man
- Owner: dreadnode
- License: other
- Created: 2024-10-24T15:07:42.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2025-02-05T16:36:54.000Z (8 months ago)
- Last Synced: 2025-07-03T09:54:38.345Z (3 months ago)
- Topics: gguf, onnx, pytorch, safetensors
- Language: Rust
- Homepage:
- Size: 130 KB
- Stars: 57
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# tensor-man
`tensor-man` is a utility to inspect, validate, sign and verify machine learning model files.
## Supported Formats
* [safetensors](https://github.com/huggingface/safetensors)
* [ONNX](https://onnx.ai/)
* [GGUF](https://huggingface.co/docs/hub/gguf)
* [PyTorch](https://pytorch.org/)
> [!IMPORTANT]
> PyTorch models are loaded and inspected in a networkless Docker container in order to prevent [unintended code execution](https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models) on the host machine.
## Install with Cargo
This is the recommended way to install and use the tool:
```bash
cargo install tensor-man
```
## Pull from Docker Hub
```bash
docker pull dreadnode/tensor-man:latest
```
## Build Docker image
To build your own Docker image for the tool, run:
```bash
docker build . -t tman
```
## Note about Docker
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:
```bash
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
```
## Build from source
Alternatively you can build the project from source, in which case you'll need to have Rust and Cargo [installed on your system](https://rustup.rs/).
Once you have those set up, clone the repository and build the project:
```bash
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:
```bash
# 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/
```
## Usage
### Inspect
Inspect a file and print a brief summary:
```bash
tman inspect /path/to/whatever/llama-3.1-8b-instruct.safetensors
```
Print detailed information about each tensor:
```bash
tman inspect /path/to/whatever/llama-3.1-8b-instruct.safetensors --detail full
```
Filter by tensor name:
```bash
tman inspect /path/to/whatever/llama-3.1-8b-instruct.onnx -D full --filter "q_proj"
```
Save the output as JSON:
```bash
tman inspect /path/to/whatever/llama-3.1-8b-instruct.gguf -D full --to-json output.json
```
### Sign and Verify
The tool allows you to generate an Ed25519 key pair to sign your models:
```bash
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):
```bash
# 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:
```bash
# 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
```
### Inference Graph
Generate a .dot file for the execution graph of an ONNX model:
```bash
tman graph /path/to/whatever/tinyyolov2-8.onnx --output tinyyolov2-8.dot
```
### More
For the full list of commands and options, run:
```bash
tman --help
# get command specific help
tman inspect --help
```
## License
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`.