51 lines
1.9 KiB
Markdown
51 lines
1.9 KiB
Markdown
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---
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license: apache-2.0
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base_model: Qwen/Qwen2.5-3B
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tags:
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- legal
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- legal-tech
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- legal-clause-analysis
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- lora
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pipeline_tag: text-generation
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language:
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- en
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---
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# qwen2.5-3b-legal-merged
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This repository contains a fine-tuned, merged version of the **Qwen2.5-3B** architecture, specifically optimized for legal domain text processing, contract deconstruction, and plain-English summary generation.
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The model consists of the base architecture integrated with custom LoRA adapters trained on a curated dataset of legal clauses, terms of service agreements, and privacy policies.
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## Model Description
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- **Developed by:** Ayush Ghatak
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- **Model Type:** Large Language Model (Causal LM)
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- **Base Model:** Qwen/Qwen2.5-3B
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- **Language(s):** English (Legal domain specialist)
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- **License:** Apache-2.0
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- **Fine-Tuning Method:** LoRA (Low-Rank Adaptation) merged directly into FP16 half-precision weights.
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### Primary Use Cases
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This model was designed and optimized to perform structured legal clause analysis split into twin streaming views:
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1. **Plain-English Summarization:** Condensing complex boilerplate legalese into highly scannable, high-quality bullet points.
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2. **Meta-Cognitive Reasoning:** Exposing an algorithmic, step-by-step cognitive roadmap identifying document type, legal parties, translating specific terms, and tracing logical breakdown.
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---
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## Intended Changes & Operational Triggers
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For best performance in legal clause deconstruction tasks, prompt the model using structured phases. It has been trained to specifically respond to structural tags like `<Reasoning>:` and `<Summary>:` to allow clean UI-layer splitting:
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### Expected Prompt/Response Layout
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```text
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[Input Text Block]
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<Reasoning>:
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1. IDENTIFY: [Document type and core legal purpose]
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2. TRANSLATE: [Extraction and definition of domain-specific legal vocabulary]
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3. COGNITIVE TRACE: [Step-by-step logic map of obligations and conditions]
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<Summary>:
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- [Core takeaway 1]
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- [Core takeaway 2]
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