--- title: README emoji: 🌖 colorFrom: yellow colorTo: indigo sdk: static pinned: false --- # LiteRT Community [LiteRT](https://ai.google.dev/edge/litert) is Google's on-device framework for high-performance ML & GenAI deployment on edge platforms. It is the improved successor to TensorFlow Lite. On this community page, you can find ready-to-run LiteRT models for a wide range of ML/AI tasks. Within this ecosystem, [LiteRT-LM](https://ai.google.dev/edge/litert-lm) specializes in cutting edge GenAI. Recognizing that LLMs now function as complex pipelines of related models rather than single standalone models, LiteRT-LM leverages LiteRT to deliver an optimized solution for running LLMs on-device. Both LiteRT and LiteRT-LM can run on a variety of devices including Android, iOS, Windows, macOS, Linux, IoT and Web allow easy deployment and scaling across a diverse device landscape. # Trying it Live
| [](https://play.google.com/store/apps/details?id=com.google.ai.edge.gallery&pli=1) | [](https://apps.apple.com/us/app/google-ai-edge-gallery/id6749645337) | [](https://ai.google.dev/edge/litert-lm/cli) | [](https://ai.google.dev/edge/litert-lm/cli) | [](https://huggingface.co/spaces/tylermullen/Gemma4) | | :---: | :---: | :---: | :---: | :---: | | [Android](https://play.google.com/store/apps/details?id=com.google.ai.edge.gallery&pli=1) | [iOS](https://apps.apple.com/us/app/google-ai-edge-gallery/id6749645337) | [Desktop](https://ai.google.dev/edge/litert-lm/cli) | [IoT](https://ai.google.dev/edge/litert-lm/cli) | [Web](https://huggingface.co/spaces/tylermullen/Gemma4) |
Not sure where to start? We recommend first trying our models in our Google AI Edge Gallery app on [Android](https://play.google.com/store/apps/details?id=com.google.ai.edge.gallery&pli=1) and [iOS](https://apps.apple.com/us/app/google-ai-edge-gallery/id6749645337). # Community Contributions Are we missing your favorite model? You can convert and run [PyTorch](https://github.com/google-ai-edge/litert-torch), [TensorFlow](https://ai.google.dev/edge/litert/models/convert_tf), or [JAX](https://ai.google.dev/edge/litert/models/convert_jax) models to the classic TFLite format using the LiteRT conversion and optimization tools. Or for LLMs, you can use the [LiteRT Torch Generative API](https://github.com/google-ai-edge/ai-edge-torch/tree/main/ai_edge_torch/generative). When your model is ready, join the LiteRT community org and upload the model here for others to try! ## Submission Guidelines * **Model Conversion:** Your model must be converted using the LiteRT-Torch or Generative API in `.tflite` or `.litertlm` formats. * **Location:** All contributions must be made in the [community contribution folder](https://huggingface.co/collections/litert-community/community-contribution) (e.g., `LiteRT-Community/community-contribution/mobile-bert`). * **Licensing:** If your model has a license, it must be either an Apache 2.0 or MIT open-source license. Models with no license are also accepted. * **Data Provenance and Privacy:** If applicable, you must include a summary of the model's training data in your submission. Additionally, you must provide confirmation that all Personally Identifiable Information (PII) has been scrubbed from the data. ## Policies & Support * **Content Policy:** All uploaded models must fully comply with the [Hugging Face content guidelines](https://huggingface.co/collections/litert-community/community-contribution). * **Community Moderation:** The Google AI Edge team will not actively moderate community contributions to this community, except for reactive removal in clear cases of spam or abuse. * **Conversion Requests:** In the event that you cannot successfully convert a `.tflite` or `.litertlm` model, you may submit a PR requesting conversion support from the LiteRT team.