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Zero
title: Vchitect 2.0 | |
emoji: 🐢 | |
colorFrom: yellow | |
colorTo: pink | |
sdk: gradio | |
sdk_version: 4.42.0 | |
app_file: app.py | |
pinned: false | |
license: apache-2.0 | |
# Vchitect-XL | |
## Installation | |
### 1. Create a conda environment and install PyTorch | |
Note: You may want to adjust the CUDA version [according to your driver version](https://docs.nvidia.com/deploy/cuda-compatibility/#default-to-minor-version). | |
```bash | |
conda create -n VchitectXL -y | |
conda activate VchitectXL | |
conda install python=3.11 pytorch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 pytorch-cuda=12.1 -c pytorch -c nvidia -y | |
``` | |
### 2. Install dependencies | |
```bash | |
pip install -r requirements.txt | |
``` | |
### 3. Install ``flash-attn`` | |
```bash | |
pip install flash-attn --no-build-isolation | |
``` | |
### 4. Install [nvidia apex](https://github.com/nvidia/apex) | |
```bash | |
pip install ninja | |
git clone https://github.com/NVIDIA/apex | |
cd apex | |
# if pip >= 23.1 (ref: https://pip.pypa.io/en/stable/news/#v23-1) which supports multiple `--config-settings` with the same key... | |
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" ./ | |
# otherwise | |
pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --global-option="--cpp_ext" --global-option="--cuda_ext" ./ | |
``` | |
## Inference | |
~~~bash | |
#easy infer | |
test_file=$1 | |
save_dir=$2 | |
ckpt_path=$3 | |
python inference.py --test_file "${test_file}" --save_dir "${save_dir}" --ckpt_path "${ckpt_path}" | |
~~~ |