Mamba Retriever
This repository contains model checkpoint for Mamba Retriever
The model architecture is built upon mamba, and is trained from mamba2-1.3b
Usage
We highly recommend creating a new conda environment first:
conda create -n mamba_retriever python=3.10.14
conda activate mamba_retriever
Then, run the following in your terminal:
git clone https://github.com/state-spaces/mamba.git
conda install cudatoolkit==11.8 -c nvidia
pip install -r requirements.txt
pip3 install torch==2.1.1 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
pip install accelerate -U
cd mamba
pip install .
Next, download and install the following two files from https://github.com/state-spaces/mamba/releases and https://github.com/Dao-AILab/causal-conv1d/releases:
mamba_ssm-2.2.2+cu118torch2.1cxx11abiFALSE-cp310-cp310-linux_x86_64.whl
causal_conv1d-1.4.0+cu118torch2.1cxx11abiFALSE-cp310-cp310-linux_x86_64.whl
You can install them using
pip install mamba_ssm-2.2.2+cu118torch2.1cxx11abiFALSE-cp310-cp310-linux_x86_64.whl
pip install causal_conv1d-1.4.0+cu118torch2.1cxx11abiFALSE-cp310-cp310-linux_x86_64.whl
Evaluation
All evaluation code and details are available at Mamba Retriever Github
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Model tree for MambaRetriever/mambaretriever-1.3b
Base model
state-spaces/mamba2-1.3b