Instructions to use litert-community/Qwen2.5-Coder-3B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT-LM
How to use litert-community/Qwen2.5-Coder-3B-Instruct 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=litert-community/Qwen2.5-Coder-3B-Instruct \ --prompt="Write me a poem"
- Notebooks
- Google Colab
- Kaggle
Commit History
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Add measured performance section (M4 Max) (#1)
- Add measured performance section (M4 Max) (7dc9ff1eabb049e27e1c945f14c75278b1829c4d) - Add measured Galaxy S26 GPU-vs-CPU rows (litert-lm 0.16.0) (151c59d115c53e5378d6f2161885ceb374a1f276) Co-authored-by: Majima <mlboydaisuke@users.noreply.huggingface.co>f02778f
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Create README.md
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Upload Qwen2.5_Coder_3B_It.litertlm
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initial commit
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