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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: apache-2.0
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+ ---
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+
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+ # GEM_Testing_Arsenal
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+
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+ Welcome to ***GEM_Testing_Arsenal***, where groundbreaking research meets practical power! This repository unveils a novel architecture for On-Device Language Models (ODLMs), straight from our paper, ["Fragile Mastery: are domain-specific trade-offs undermining On-Device Language Models?"](./link_to_be_insterted). With just a few lines of code, our custom `gem_trainer.py` script lets you train ODLMs that are more accurate than ever, tracking accuracy and loss as you go.
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+
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+ ---
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+
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+ ### Highlights:
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+ - **Next-Level ODLMs**: Boosts accuracy with a new architecture from our research.
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+ - **Easy Training**: Call run_gem_pipeline to train on your dataset in minutes.
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+ - **Live Metrics**: Get accuracy and loss results as training unfolds.
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+ - **Flexible Design**: Works with any compatible dataset—plug and play!
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+
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+ ---
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+ ### Prerequisites:
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+ To dive in, you’ll need:
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+ - **Python** `3.8+`
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+
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+ - Required libraries (go through [quick start](#quick-start) below 👇)
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+
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+ - **Git** *(to clone the repo)*
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+
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+ ---
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+ ### Quick Start:
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+
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+ 1. **Clone the repository:**
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+ ```bash
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+ git clone https://huggingface.co/GEM025/GEM_banking77
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+ ```
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+
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+ 2. **Install Dependencies:**
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+ ```pwsh
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+ pip install -r requirements.txt
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+ ```
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+
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+ 3. **Train Your Model:**
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+ Create a new python file and execute the code like:
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+ ```python
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+ from datasets import load_dataset
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+ from gem_trainer import run_gem_pipeline
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+
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+ # Load a dataset (e.g., Banking77) {just replace the dataset here.}
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+ dataset = load_dataset("banking77")
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+
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+ # Train the ODLM
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+ results = run_gem_pipeline(dataset, num_classes=77)
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+
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+ print(results) # See accuracy and loss
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+ ```
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+
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+ > ***Boom—your ODLM is training with boosted accuracy!***
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+
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+ ---
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+ ### Customizing Training:
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+ `run_gem_pipeline` keeps it simple, but you can tweak it! Dive into [`gem_trainer.py`](./gem_trainer.py) to adjust epochs, batch size, or other settings to fit your needs.
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+
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+ ---
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+ ### Contributing 💓
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+ Got ideas to make this even better? We’re all ears!
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+ - Fork the repo.
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+ - Branch off (`git checkout -b your-feature`).
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+ - Submit a pull request with your magic.
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+
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+ ---