Practical overview
When it fits
Use Openchat when you want to explore its language models or need repository-documented paths for inference, benchmark evaluation or training.
Who it is for
- People who want to try Openchat models through the linked online demo.
- Developers seeking documented options for running models locally or serving them through an API.
- Researchers and practitioners interested in reproducing benchmarks or training models on mixed-quality data.
Documented uses
- Explore Openchat models through the online demo.
- Run model inference using the documented API server or Transformers path.
- Reproduce documented benchmarks for a selected model.
- Train using supported Llama 3 or Mistral base models and Openchat’s training system.
Requirements & limits
- Local installation requires PyTorch and CUDA; the repository documents pip installation and a Python 3.11 conda setup.
- The optimized API server uses vLLM; the repository says Transformers inference is slower.
- The documented training workflow depends on selecting compatible base-model weights, model type, batch size and conversation-template tokens.
- Licensing differs across listed model versions: OpenChat 3.5 is listed as Apache 2.0, while OpenChat 3.6 is listed with a Llama 3 license.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Install OpenChat from its Python package
Install the OpenChat package in a Conda environment.
Before you start
- PyTorch and CUDA are needed to run OpenChat.
- Conda and Python 3.11.
Steps
Create a Conda environment with Python 3.11:
conda create -y --name openchat python=3.11.Activate it with
conda activate openchat.Install OpenChat with the command below.
pip3 install ochat
Expected outcome
The `ochat` package is installed in the `openchat` Conda environment.
Guide limitations
- The installation steps do not document a model run or inference workflow.
- The README notes that pip package compatibility issues may occur; it suggests trying the Conda method or consulting the linked issue.
Install OpenChat from source in editable mode
Clone the OpenChat repository and install it in editable mode.
Before you start
- PyTorch and CUDA are needed to run OpenChat.
- Git and pip.
Steps
Clone the repository: the command below.
git clone https://github.com/imoneoi/openchatChange into the repository directory:
cd openchat.Upgrade pip to enable PEP 660 support: the command below.
pip3 install --upgrade pipInstall the project in editable mode: the command below.
pip3 install -e .
Expected outcome
OpenChat is installed in editable mode from the cloned repository, allowing changes in that clone.
Guide limitations
- The installation instructions do not document a model run or inference workflow.
Compare options for Model inference and serving
These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.
| Project | Documented purpose | Platform | Access and requirements |
|---|---|---|---|
| Openchat | Explore Openchat models through the online demo. | Web | |
| Pulse Of Motion | Estimate a video's physical frame rate from its visual dynamics. | Linux | The repository is public. Its README describes a released checkpoint that downloads from Hugging Face on first inference, with a manual download option. The strongest internal model is not fully released; the README directs interested users to contact the project about access. No license information is provided in the repository evidence. |
| Neural Image Assessment | Train the model using AVA images and rating annotations. | Cloud, Linux, macOS, Windows |
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 16 October 2026
- Original website title
- imoneoi/openchat · Official homepage title · retained in its source language