Instructions to use eye-v/skyle-ai-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use eye-v/skyle-ai-models 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
- LiteRT-LM
How to use eye-v/skyle-ai-models 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=eye-v/skyle-ai-models \ --prompt="Write me a poem"
- Notebooks
- Google Colab
- Kaggle
Switch web build to gemma-4-E2B-it-web.litertlm (LiteRT-LM web path)
Browse files- .gitattributes +1 -0
- README.md +1 -1
- gemma-4-E2B-it-web.litertlm +3 -0
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README.md
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| `gemma-4-E2B-it.litertlm` | 2 588 147 712 B (~2.6 GB) | iOS / Android / desktop (LiteRT-LM) |
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## License notice
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| `gemma-4-E2B-it-web.litertlm` | 2 008 432 640 B (~1.87 GiB) | Web (LiteRT-LM, WebGPU) |
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## License notice
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