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README.md
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license: mit
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tags:
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- coreml
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- ANE
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- DeepSeek
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- Apple
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focused on accelerating the porting of Large Language Models (LLMs)
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running on ANE.
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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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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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License
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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 3.1 8B architecture and may require a separate license.
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This test model is exclusively for the
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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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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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pip install coremltools transformers
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How to RUN:
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python chat.py
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Ctr-D to exit, Ctr-C to interrupt inference.
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python chat.py Q123 -d /path/to/anemll-DeepSeek-8B-ctx1024 ctx=1024
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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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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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---
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license: mit
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tags:
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- coreml
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- ANE
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- DeepSeek
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- Apple
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- Apple Neural Engine
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---
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# ANEMLL
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**ANEMLL** (pronounced like “animal”) is an open-source project focused on accelerating the porting of Large Language Models (LLMs) to tensor processors, starting with the Apple Neural Engine (ANE).
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The goal is to provide a fully open-source pipeline from model conversion to inference for common LLM architectures running on ANE.
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This enables seamless integration and on-device inference for low-power applications on edge devices, ensuring maximum privacy and security.
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This is critical for autonomous applications, where models run directly on the device without requiring an internet connection.
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---
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## License
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ANEMLL is licensed under the [MIT License](https://opensource.org/license/mit).
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The model is based on Meta’s LLaMA 3.1 8B architecture and may require a separate license.
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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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## 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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`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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**Installation**
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Unzip all ZIP files with CoreML Models files using Finder or via bash
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```bash
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cd ./anemll-DeepSeek-8B-ctx1024
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find . -type f -name "*.zip" -exec unzip {} \;
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```
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```bash
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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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Ctr-D to exit, Ctr-C to interrupt inference.
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**Alternative way to run:**
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```bash
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python chat.py Q123 -d /path/to/anemll-DeepSeek-8B-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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** More Info **
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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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