MAV
Project description
Introduction
MAV
Getting started
If uv is installed:
uv run --with openmav mav
or
uv run --with git+https://github.com/attentionmech/mav mav --model gpt2 --prompt "hello mello"
Without uv:
-
Set up and activate a virtual environment
-
Install the package:
pip install openmav
or
pip install git+https://github.com/attentionmech/mav
-
Run:
mav --model gpt2 --prompt "hello mello"
-
or Import
from openmav.mav import MAV MAV("gpt2", "Hello")
Locally from scratch
- git clone https://github.com/attentionmech/mav
- cd mav
- Set up and activate a virtual environment
- Install the package:
pip install .
- Run:
mav --model gpt2 --prompt "hello mello"
You can replace gpt2 with other Hugging Face models for example:
meta-llama/Llama-3.2-1BHuggingFaceTB/SmolLM-135Mgpt2-mediumgpt2-large
UI
Examples
running MAV with a training loop with a custom model (not pretrained one)
uv run examples/vis_train_loop.py
Demos
Note: explore it using the command line help as well, since many sampling params are exposed.
Project details
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