Instructions to use DarrenJiaImbue/gemma-4-e4b-it-bouncer-litertlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT-LM
How to use DarrenJiaImbue/gemma-4-e4b-it-bouncer-litertlm 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 litert-lm # 2. Download and run this model locally: # See: https://ai.google.dev/edge/litert-lm/cli litert-lm run \ --from-huggingface-repo=DarrenJiaImbue/gemma-4-e4b-it-bouncer-litertlm \ model.litertlm \ --prompt="Write me a poem"
- Notebooks
- Google Colab
- Kaggle
Dual-signature export v4: dropped pre_lower_decomp/torch_tfl.decomps from eager trace path (was baking in INT32/INT64 mixed-type CONCATENATION ops that TFLite rejects at compile time). Runtime verified: classifier path returns 4 logits per prompt; same values as single-sig.
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