Instructions to use apbaxel/gemma-3-270m-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT-LM
How to use apbaxel/gemma-3-270m-it with LiteRT-LM:
# LiteRT-LM runs on various platforms (Android, iOS, Windows, Linux, macOS, IoT, Web/WASM) # and supports many APIs (C++, Python, Kotlin, Swift, JavaScript, Flutter). # For platform-specific integration guides, please refer to the official developer website: # https://ai.google.dev/edge/litert-lm # To try LiteRT-LM, the easiest way is to use our CLI tool. # 1. Install the LiteRT-LM CLI tool: pip install -U litert-lm # 2. Download and run this model locally: # See: https://ai.google.dev/edge/litert-lm/cli litert-lm run \ --from-huggingface-repo=apbaxel/gemma-3-270m-it \ --prompt="Write me a poem"
- Notebooks
- Google Colab
- Kaggle
Gemma 3 270M IT โ q8 LiteRT-LM
Mirror of litert-community/gemma-3-270m-it:gemma3-270m-it-q8.litertlm (304005120 B, int8 weight-only, float KV, generic CPU).
Gemma is provided under and subject to the Gemma Terms of Use found at https://ai.google.dev/gemma/terms
This is a Model Derivative โ Prohibited Use Policy (https://ai.google.dev/gemma/prohibited_use_policy) and all distribution conditions in ยง3.1 apply.
Original: https://huggingface.co/litert-community/gemma-3-270m-it
Base: https://huggingface.co/google/gemma-3-270m-it
File: gemma3-270m-it-q8.litertlm (CPU litertlm; not .task / mediatek / qualcomm NPU variants)
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