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Model: ayushhh1662309/qwen2.5-3b-legal-merged
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen2.5-3B
+tags:
+- legal
+- legal-tech
+- legal-clause-analysis
+- lora
+pipeline_tag: text-generation
+language:
+- en
+---
+
+# qwen2.5-3b-legal-merged
+
+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.
+
+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.
+
+## Model Description
+
+- **Developed by:** Ayush Ghatak
+- **Model Type:** Large Language Model (Causal LM)
+- **Base Model:** Qwen/Qwen2.5-3B
+- **Language(s):** English (Legal domain specialist)
+- **License:** Apache-2.0
+- **Fine-Tuning Method:** LoRA (Low-Rank Adaptation) merged directly into FP16 half-precision weights.
+
+### Primary Use Cases
+This model was designed and optimized to perform structured legal clause analysis split into twin streaming views:
+1. **Plain-English Summarization:** Condensing complex boilerplate legalese into highly scannable, high-quality bullet points.
+2. **Meta-Cognitive Reasoning:** Exposing an algorithmic, step-by-step cognitive roadmap identifying document type, legal parties, translating specific terms, and tracing logical breakdown.
+
+---
+
+## Intended Changes & Operational Triggers
+
+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:
+
+### Expected Prompt/Response Layout
+```text
+[Input Text Block]
+
+<Reasoning>:
+1. IDENTIFY: [Document type and core legal purpose]
+2. TRANSLATE: [Extraction and definition of domain-specific legal vocabulary]
+3. COGNITIVE TRACE: [Step-by-step logic map of obligations and conditions]
+
+<Summary>:
+- [Core takeaway 1]
+- [Core takeaway 2]