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- license: mit
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+ ANEMLL
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+
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+ ANEMLL (pronounced like “animal”) is an open-source project
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+ focused on accelerating the porting of Large Language Models (LLMs)
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+ to tensor processors, starting with the Apple Neural Engine (ANE).
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+
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+ The goal is to provide a fully open-source pipeline
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+ from model conversion to inference for common LLM architectures
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+ running on ANE.
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+
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+ This enables seamless integration and on-device inference
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+ for low-power applications on edge devices,
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+ ensuring maximum privacy and security.
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+
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+ This is critical for autonomous applications,
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+ where models run directly on the device
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+ without requiring an internet connection.
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+
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+ License
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+
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+ ANEMLL is licensed under the MIT License.
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+ https://opensource.org/license/mit
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+ The model is based on Meta’s LLaMA 3.2 and may require a separate license.
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+
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+
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+ This test model is exclusively for the Meta's LLaMA 3.2 1B (1024 context) model converted for CoreML,
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+ released before the official launch of the ANEMLL repository and minimal documentation.
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+ It is intended for early adopters only who requested an early release.
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+
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+
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+ Requirements
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+ • macOS Sequoia with Apple Neural Engine and 16GB RAM
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+ • CoreML Tools and HuggingFace Transformers libraries
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+ • Python 3.9
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+
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+ chat.py provides a sample inference script.
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+ We apologize for the current quality of chat.py and appreciate your patience.
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+
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+
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+ Prerequisites:
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+ pip install coremltools transformers
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+
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+ How to RUN:
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+ python chat.py
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+
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+ Ctr-D to exit, Ctr-C to interrupt inference.
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+
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+ alternative way to run:
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+ python chat.py S123 -d /path/to/anemll-LLAMA32-1B-ctx1024 ctx=1024
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+
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+ The first time the model loads, macOS will take some time to place it on the device.
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+ Subsequent loads will be instantaneous.
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+
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+ Please check following links for later updates:
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+ https://huggingface.co/anemll
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+ https://x.com/anemll
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+ https://github.com/anemll
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+ https://anemll.com
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