# Embeddings You can manage your available embeddings through the application settings. ![Open settings](/talemate/img/0.26.0/open-settings.png) In the settings dialogue go to **:material-tune: Presets** and then **:material-cube-unfolded: Embeddings**. ## Pre-configured Embeddings ### all-MiniLM-L6-v2 The default ChromaDB embedding. Also the default for the Memory agent unless changed. Fast, but the least accurate. ### Alibaba-NLP/Gte-Base-En-V1.5 Sentence transformer model that is decently fast and accurate and will likely become the default for the Memory agent in the future. ### Instructor Models !!! warning "Support of these likely deprecated" Its become increasingly difficult to install support for these while keeping other dependencies up to date. See [this issue](https://github.com/vegu-ai/talemate/issues/176) for more details. Use the `Alibaba-NLP/Gte-Base-En-V1.5` embedding instead, its pretty close in accuracy and much smaller. Instructor embeddings, coming in three sizes: `base`, `large`, and `xl`. XL is the most accurate but also has the biggest memory footprint and is the slowest. Using `cuda` is recommended for the `xl` and `large` models. ### OpenAI text-embedding-3-small OpenAI's current text embedding model. Fast and accurate, but not free. ## Adding an Embedding You can add new embeddings by clicking the **:material-plus: Add new** button. Select the embedding type and then enter the model name. When using sentence-transformer, make sure the modelname matches the name of the model repository on Huggingface, so for example `Alibaba-NLP/gte-base-en-v1.5`. ![Add new embedding](/talemate/img/0.27.0/embedding-settings-new-1.png) !!! warning "New embeddings require a download" When you add a new embedding model and use it for the first time in the Memory agent, Talemate will download the model from Huggingface. This can take a while, depending on the size of the model and your internet connection. You can track the download in the talemate process window. A better UX based download progress bar is planned for a future release. ## Editing an Embedding ![Edit embedding](/talemate/img/0.27.0/embedding-settings-edit.png) Select the existing embedding from the left side bar and you may change the following properties: ##### Trust Remote Code For custom sentence-transformer models, you may need to toggle this on. This can be a security risk, so only do this if you trust the model's creator. It basically allows remote code execution. !!! warning Only trust models from reputable sources. ##### Device The device to use for the embeddings. This can be either `cpu` or `cuda`. Note that this can also be overridden in the Memory agent settings. ##### Distance The maximum distance for results to be considered a match. Different embeddings may require different distances, so if you find low accuracy, try changing this value. ##### Distance Mod A multiplier for the distance. This can be used to fine-tune the distance without changing the actual distance value. Generally you should leave this at 1. ##### Distance Function The function to use for calculating the distance. The default is `Cosine Similarity`, but you can also use `Inner Product` or `Squared L2`. The selected embedding may require a specific distance function, so if you find low accuracy, try changing this value. ##### Fast This is just a tag to mark the embedding as fast. It doesn't actually do anything, but can be useful for sorting later on. ##### GPU Recommendation This is a tag to mark the embedding as needing a GPU. It doesn't actually do anything, but can be useful for sorting later on. ##### Local This is a tag to mark the embedding as local. It doesn't actually do anything, but can be useful for sorting later on.