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--- |
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license: llama3.2 |
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language: |
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- en |
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base_model: |
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- meta-llama/Llama-3.2-1B-Instruct |
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tags: |
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- legal |
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--- |
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We have successfully developed and trained a custom Large Language Model (LLM) tailored specifically for SpeedLegal's needs. This model, based on the Llama 3.2 1B architecture, has been fine-tuned on CUAD (Contract Understanding Atticus Dataset) dataset to enhance our ability to analyse and highlight critical sections of legal documents that require lawyer review. |
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# Key Features |
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1.Specialised Legal Focus: Our model is trained to understand and process complex legal language and contexts. |
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2.Efficient and Lightweight: Built on a 1 billion parameter base model, it balances performance with computational efficiency. |
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3.Custom Training: Fine-tuned on our dataset of legal documents, questions, and expert-annotated answers. |
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4.Scalable Solution: Designed to handle a wide range of legal document types and queries. |
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# Technical Highlights |
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1. Base Model: Llama 3.2 1B, a state-of-the-art language model known for its efficiency and performance. |
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2. Training Data: Utilised our self curated CUAD dataset, enhancing the model's relevance to our specific use cases. |
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3. Fine-tuning Technique: Employed Parameter-Efficient Fine-Tuning (PEFT) with LoRA (Low-Rank Adaptation) for optimal performance and resource utilisation. |
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4. Performance Monitoring: Integrated with Weights & Biases (wandb) for comprehensive tracking of training metrics and model performance. |
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# Business Impact |
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1. Increased Efficiency: Automates the initial review process, allowing lawyers to focus on critical sections identified by the model. |
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2. Improved Accuracy: Trained on expert-annotated data, the model can identify subtle legal nuances that general-purpose models might miss. |
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3. Scalability: Can process large volumes of legal documents quickly, supporting our growth and handling increased workloads. |
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4. Competitive Advantage: Positions SpeedLegal at the forefront of AI-driven legal tech, offering unique value to our clients. |
