Instructions to use aoiandroid/streamgemma-2.2b-litert-lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use aoiandroid/streamgemma-2.2b-litert-lm with LiteRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
StreamGemma-2.2B LiteRT-LM
This is the quantized, LiteRT-LM format package of the unreduced 2.21B parameter StreamGemma model. The model features dynamic range INT8 quantization and is optimized for ultra-low latency streaming inference on edge devices (Android, etc.).
Model Details
- Architecture: StreamGemma-Nano v2
- Parameters: 2.21B backbone
- Format: LiteRT / TFLite Flatbuffers (INT8 Quantized)
- Component Files:
audio_model.tflite: Handles PCM audio inputs (1.6GB)text_model.tflite: Handles tokenized text inputs (2.6GB)vision_model.tflite: Handles vision patch embeddings (2.6GB)draft_model.tflite: Speculative decoding draft module (2.6GB)
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