BasicAI now supports custom model integration via [API](https://docs.basic.ai/reference/post_image-detection), tailored to meet your unique model annotation requirements. *** # 1\. Create a Model Head to **the Model Center** - **My Models** and click the `+ Create` button. You can create a model by yourself or by Hugging Face. ## 1.1 By Myself Under the tab `By Myself`, fill in the following information: * **Model Name:** Input the name of your model, which can be edited later. * **Data Type:** Currently, BasicAI only supports custom models targeting `Image` data and Point Cloud Data (PCDs) in `LiDAR Fusion` data. * **Task Type:** Select whether to detect objects or segment data. The `Detection` mode exclusively supports 2D bounding box annotation for Image data and cuboid (3D box) annotation for PCDs in LiDAR Fusion data. * **Thumbnail:** Optionally upload a cover image of the model (max 5MB). Click `OK` to complete creation. ![](https://files.readme.io/d714ee8-image.png) ## 1.2 By Hugging Face 🤗 Hugging Face is an open-source community platform for AI, where users can publish and share pre-trained models. It is currently the largest open-source model community. By accessing Hugging Face, users can access hundreds or thousands of models at very low cost or even for free. If you want to create a model by Hugging Face, please switch to the `By Hugging Face` tab, fill in the following information and then click `OK`: * **Hosted Interface API**: which is all kinds of Hugging Face URLs or repo\_id. * **Access Token**: which is generated on Hugging Face. ![](https://files.readme.io/17b9363-image.png) How to get those key fields from Hugging Face to create a model on BasicAI? You can refer to this documentation of [detailed parameters](https://huggingface.co/docs/api-inference/detailed_parameters) on Hugging Face. *** # 2\. Self-Created Model Setting ## 2.1 Model Configuration First, click the edit icon to input your model API URL. The *Request Method* is fixed as `POST`. BasicAI will send a data sample from your team datasets to test the model connection. An example Request Body will be automatically provided in JSON format (read-only). Optionally, you can input `Authorization` in the Header if needed. Then, click the `Test Connection` button. You will see the *Request Status* and the *Response*. If you encounter any errors, please follow the instructions provided in the prompt. Upon successful testing, click `Save`. > 🚧 For more information, please review [the API Reference](https://docs.basic.ai/reference/post_image-detection).

## 2.2 Class Configuration Click `Config Classes`to match the ID with the model Class. * **ID:** The class or label in your API response. * **Class:** The class name shown for the model in BasicAI.

You can switch between `Edit by row` or `Edit by text` in the top right corner of the pop-up window. * **Edit by row:** Input the corresponding ID and Class at each row. * **Edit by text:** Input “ID,Name” for each pair.

annotate data, data labeling, annotation tool, model, machine learning

Edit by row

Edit by text

> 🚧 Remember to save. > > Click `OK` to save your edits. Otherwise, the changes will be lost. *** # 3\. Hugging Face Model Setting After you create a model by Hugging Face, the pre-configured classes in the Hugging Face model will be displayed on the setting page. On this page, you can operate the following options: * **Changing Access Tokens**: you can click the pencil icon beside the access token to edit it if needed. * **Changing Model Name**: click the editing icon beside the model name on the left side to change the model name. * **Reset Classes**: click the refresh icon beside classes to reset the classes and fetch the latest class information from Hugging Face. Please note that this may cause inconsistency with your model mapping. * **Delete Model**: You can click the `Delete` button at the bottom to delete the model. Please operate with caution. ![](https://files.readme.io/c724d59-image.png) # 4\. Run the Model The icons next to the Model and Class Configuration indicate their status. When both turn green, you can click `Run Model` at the top right corner. The model running process is similar to [Pre-trained Models](https://docs.basic.ai/docs/model).

> ❗️ Be cautious to delete. > > Deleting the model will remove the model itself and all associated model run results in the dataset. Objects directly generated in tools will not be affected.