🛠️ 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 -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.txt
```

The

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

Additional Instructions

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.

🛠️ 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 -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.txt
```

The

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

Additional Instructions

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'

setup.py

and then recompiling.

🛠️ Installation

🛠️ Installation

Additional Instructions

Related Skills

<h1 align="center">

- Identify gaps

2. Apply Deepthink Protocol (reason about dependencies

🛠️ Installation

Additional Instructions