Instructions to use NeuML/gemma-4-tiny-random-litert-lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT-LM
How to use NeuML/gemma-4-tiny-random-litert-lm 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=NeuML/gemma-4-tiny-random-litert-lm \ model.litertlm \ --prompt="Write me a poem"
- Notebooks
- Google Colab
- Kaggle
Model Card for Gemma 4 LiteRT-LM
Tiny randomly initialized Gemma 4 LiteRT-LM model for testing.
Created using the following code.
# pip install litert-torch
from litert_torch.generative.export_hf.export import export
export(
model="optimum-intel-internal-testing/tiny-random-gemma4",
output_dir="output",
externalize_embedder=True,
# Disable quantization, None still defaults to a value
quantization_recipe="",
use_jinja_template=False,
)
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