Practical overview
When it fits
Use it when you need a customizable code framework for multimodal model training and feedback-based alignment, and can provide the compute environment required for your chosen setup.
Who it is for
- AI researchers developing multimodal alignment experiments
- Developers customizing model fine-tuning and feedback-based training workflows
Documented uses
- Fine-tune multimodal models with feedback-based alignment methods.
- Explore or compare SFT, DPO and PPO training workflows.
- Develop alignment experiments involving image, video or audio modalities.
- Adapt training code for vision-language and vision-language-action models.
Requirements & limits
The repository is public on GitHub and licensed under Apache-2.0.
- The setup instructions describe Nvidia GPU and Huawei Ascend NPU paths, with different Python and dependency details.
- CUDA is described as optional but recommended for the Nvidia path; vLLM 0.7.2 is an additional install for PPO with the vLLM engine.
- The framework exposes training scripts, tutorials and documentation, so users can choose a workflow suited to their modality and method.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Set up Align Anything in a Conda environment
Prepare the repository for development using the documented Nvidia GPU setup path.
Before you start
- Git access to the public repository
- Conda
- Python 3.11
Steps
Clone the Align Anything repository and change into its directory.
Create and activate a Conda environment with Python 3.11.
For Nvidia GPU use, optionally install CUDA in the environment and set CUDA_HOME as described in the README.
Install the repository in editable mode with pip3 install -e .
For PPO using the vLLM engine, install the listed vLLM version, 0.7.2.
Expected outcome
The repository is installed in editable mode in the Conda environment; the README identifies vLLM as an extra for PPO with that engine.
Guide limitations
- The README's CUDA example was tested on an H800 cluster and says the CUDA version may need adjustment for the computing cluster.
- These steps cover installation, not running a training job.
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 3 November 2026
- Original website title
- PKU-Alignment/align-anything · Official homepage title · retained in its source language