General
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- Clone this repository:
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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 -y 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.txtThe
clip_benchmark.txt is not included in the default installation. If you require the clip_benchmark functionality, please install it manually by running the following command:
pip install -r requirements/clip_benchmark.txt
Install
flash-attn==2.3.6:
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.
<img src=https://github.com/OpenGVLab/InternVL/assets/23737120/c04a989c-8024-49fa-b62c-2da623e63729 width=50%>