Instructions to use Milewuigrhi3/evie-compact-tier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT-LM
How to use Milewuigrhi3/evie-compact-tier 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 # A single .litertlm file in the repo is picked automatically; otherwise the CLI asks which one to run # (or pass its name right after the repo id). litert-lm run \ --from-huggingface-repo=Milewuigrhi3/evie-compact-tier \ --prompt="Write me a poem"
- Notebooks
- Google Colab
- Kaggle
evie-compact-tier โ Evie mirror
The on-device models for Evie's compact tier (iPhone and iPad with 4 GB of memory), re-hosted for availability and immutable pinning. Files are unmodified.
| File | Source | sha256 |
|---|---|---|
gemma-4-E2B-it.litertlm |
litert-community/gemma-4-E2B-it-litert-lm @ b3ca0d2f076785a8f4b2219ddbd2bdb99954eae1 |
181938105e0eefd105961417e8da75903eacda102c4fce9ce90f50b97139a63c |
kokoro/model.onnx |
csukuangfj/kokoro-multi-lang-v1_0 @ f7b96bb6bef5c5da4d3aa4f4e0498fbbf62dc78b (k2-fsa export of Kokoro v1.0, fp32) |
b40f62b166ac8164b0627ef48a0b358eda0985e272fb03ef5252e7206305da11 |
Gemma 4 is released by Google under the Apache License 2.0; "Gemma" is a trademark of Google LLC. Kokoro-82M is by hexgrad, Apache License 2.0. Not affiliated with or endorsed by Google, hexgrad or k2-fsa.
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