The model is converted from the original LocoreMind/LocoOperator-4B using:
litert-torch export_hf \
--model=LocoreMind/LocoOperator-4B \
--output_dir="./dynamic_wi8_afp32" \
--quantization_recipe="dynamic_wi8_afp32" \
--bundle_litert_lm=true
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Model tree for 4ntoine/LocoOperator-4B-LiteRTLM
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Qwen/Qwen3-4B-Instruct-2507 Finetuned
LocoreMind/LocoOperator-4B
# 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=4ntoine/LocoOperator-4B-LiteRTLM \ --prompt="Write me a poem"