| ## Typesense Public Embedding Models | |
| We maintain a repository of currently supported embedding models, and we welcome contributions from the community. If you have a model that you would like to add to our supported list, you can convert it to the ONNX format and create a Pull Request (PR) to include it. | |
| ### Convert a model to ONNX format | |
| #### Converting a Hugging Face Transformers Model | |
| To convert any model from Hugging Face to ONNX format, you can follow the instructions in [this link](https://huggingface.co/docs/transformers/serialization#export-to-onnx) using the ```optimum-cli```. | |
| #### Converting a PyTorch Model | |
| If you have a PyTorch model, you can use the ```torch.onnx``` APIs to convert it to the ONNX format. More information on the conversion process can be found [here](https://pytorch.org/docs/stable/onnx.html). | |
| #### Converting a Tensorflow Model | |
| For Tensorflow models, you can utilize the tf2onnx tool to convert them to the ONNX format. Detailed guidance on this conversion can be found [here](https://onnxruntime.ai/docs/tutorials/tf-get-started.html#getting-started-converting-tensorflow-to-onnx). | |
| ### Creating model config | |
| Before submitting your ONNX model through a PR, you need to organize the necessary files under a folder with the model's name. Ensure that your model configuration adheres to the following structure: | |
| - **Model File**: The ONNX model file. | |
| - **Vocab File**: The vocabulary file required for the model. | |
| - **Model Config File**: Named as config.json, this file should contain the following keys: | |
| | Key | Description | Optional | | |
| |-----|-------------|----------| | |
| |model_md5| MD5 checksum of model file as string| No | | |
| |vocab_md5| MD5 checksum of vocab file as string| No | | |
| |model_type| Model type (currently only ```bert``` and ```xlm_roberta``` supported)| No | | |
| |vocab_file_name| File name of vocab file| No | | |
| |indexing_prefix| Prefix to be added before embedding documents| Yes | | |
| |query_prefix| Prefix to be added before embedding queries | Yes | | |
| Please make sure that the information in the configuration file is accurate and complete before submitting your PR. | |
| We appreciate your contributions to expand our collection of supported embedding models! | |