Metadata-Version: 2.3
Name: easyroutine
Version: 0.3.2
Summary: 
Author: Francesc0rtu
Author-email: francescortu@live.it
Requires-Python: >=3.10,<4.0
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Requires-Dist: accelerate (>=1.1.1,<2.0.0)
Requires-Dist: einops (>=0.8.0,<0.9.0)
Requires-Dist: numpy (>=2.1.3,<3.0.0)
Requires-Dist: pandas (>=2.0.0,<3.0.0)
Requires-Dist: pytest (>=8.3.3,<9.0.0)
Requires-Dist: python-dotenv (>=1.0.1,<2.0.0)
Requires-Dist: pyyaml (>=6.0.2,<7.0.0)
Requires-Dist: rich (>=13.9.4,<14.0.0)
Requires-Dist: sentencepiece (>=0.2.0,<0.3.0)
Requires-Dist: torch (==2.4.0)
Requires-Dist: torchvision (>=0.19,<0.20)
Description-Content-Type: text/markdown

# EasyRoutine

This is just a simple collection of routines that I use frequently. I have found that I often need to do the same things over and over again, so I have created this repository to store them. I hope you find them useful.

## Installation


## Interpretability
The interpretability module contains wrapper of huggingface LLM/VLM that help to perform interpretability tasks on the model. Currently, it supports:
- Extract activations of any component of the model
- Perform ablation study on the model during inference
- Perform activation patching on the model during inference

### Load the model
```python
from easyroutine.interpretability import HookedModel
```
