Installation

Installation#

  • Clone this repository:

    git clone https://github.com/OpenGVLab/InternVL.git

  • Create a conda virtual environment and activate it:

    conda create -n internvl python=3.9
conda activate internvl

  • Install dependencies using requirements.txt:

    pip install -r requirements.txt

    By default, our requirements.txt file includes the following dependencies:

    • -r requirements/internvl_chat.txt

    • -r requirements/streamlit_demo.txt

    • -r requirements/classification.txt

    • -r requirements/segmentation.txt

    The clip_benchmark.txt is not included in the default installation. If you require the clip_benchmark functionality (for the evaluation of zero-shot classification or retrieval), please install it manually by running the following command:

    pip install -r requirements/clip_benchmark.txt

Additional Instructions#

  • Install flash-attn==2.3.6 (optional, for training chat models):

    pip install flash-attn==2.3.6 --no-build-isolation

    Alternatively you can compile from source:

    git clone https://github.com/Dao-AILab/flash-attention.git
cd flash-attention
git checkout v2.3.6
python setup.py install

  • Install mmcv-full==1.6.2 (optional, for segmentation):

    pip install -U openmim
mim install mmcv-full==1.6.2

  • Install apex (optional, for segmentation):

    git clone https://github.com/NVIDIA/apex.git
git checkout 2386a912164b0c5cfcd8be7a2b890fbac5607c82  # https://github.com/NVIDIA/apex/issues/1735
pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" ./

    If you encounter ModuleNotFoundError: No module named 'fused_layer_norm_cuda', it is because apex’s CUDA extensions are not being installed successfully. You can try uninstalling apex and the code will default to the PyTorch version of RMSNorm. Alternatively, if you prefer using apex, try adding a few lines to setup.py and then recompiling.



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