RBDash

Install

1. Clone this repository and navigate to RBDash folder

git clone https://github.com/rbdash.git
cd RBDash

2. Install Package

conda create -n rbdash python=3.10 -y
conda activate rbdash
pip install --upgrade pip  # enable PEP 660 support
pip install -e .

3. Install additional packages for training cases

pip install ninja
pip install flash-attn --no-build-isolation

Upgrade to latest code base

git pull
pip uninstall transformers
pip install -e .

Model Zoo

RBDash-v1-13b

Evaluation

In RBDash, we evaluate models on MME.

MME

1. Download the data following the official instructions here.
2. Downloaded images to ./playground/data/eval/MME/MME_Benchmark_release_version.
3. Downloaded and put the weights to ./models/rbdash-v1-13b
4. Single-GPU inference and evaluate.

CUDA_VISIBLE_DEVICES=0 bash scripts/v1/eval/mme.sh