truss
**Truss: Model Packaging & Deployment**
**Overview**
Truss is an open-source framework (by Baseten) for packaging AI/ML models. It solves the "it works on my machine" problem for ML models by creating a standardized structure that runs locally and deploys anywhere (Docker).
**The Problem**
Deploying a model requires:
- Correct Python version.
- System packages (apt-get install libGL).
- Python requirements (pip install torch).
- Serialization checks.
Truss handles this automatically.
**How to use**
```bash
pip install truss
```
```python
import truss
from transformers import pipeline
# Load model
pipe = pipeline("text-classification")
# Create truss
truss.create(pipe, target_directory="./my-model")
```
This creates a folder with:
- `model/model.py`: Inference logic.
- `config.yaml`: Dependencies and settings.
- `data/`: Model weights.
**Live Reload**
Truss supports "live reload" during development. You can tweak the `model.py` code and verify the API response instantly in Docker without rebuilding the image from scratch.
**Deployment**
- **Baseten**: Native deployment (one click).
- **Docker**: `truss build-image ./my-model` → deploy to AWS/GCP.
Truss is a modern alternative to BentoML, focusing on developer experience and rapid iteration.