Haikal1506/qwen2.5-7b-legal-finetuned

TEXT GENERATIONConcurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jun 21, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

Haikal1506/qwen2.5-7b-legal-finetuned is a 7.6 billion parameter Qwen2.5 model developed by Haikal1506. This model is specifically fine-tuned for legal applications, leveraging the Qwen2.5-7B-Instruct-bnb-4bit base. It was trained using Unsloth and Huggingface's TRL library, enabling faster fine-tuning for specialized legal tasks.

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Model Overview

Haikal1506/qwen2.5-7b-legal-finetuned is a specialized language model developed by Haikal1506. It is based on the Qwen2.5 architecture, specifically fine-tuned from the unsloth/Qwen2.5-7B-Instruct-bnb-4bit model. With 7.6 billion parameters, this model is designed for applications requiring expertise in the legal domain.

Key Characteristics

  • Base Model: Qwen2.5-7B-Instruct-bnb-4bit, a robust instruction-tuned model.
  • Fine-tuning: Optimized for legal applications, suggesting enhanced performance on legal texts and queries.
  • Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitates faster training processes.

Intended Use Cases

This model is particularly well-suited for tasks within the legal sector. Potential applications include:

  • Legal Document Analysis: Summarizing legal texts, extracting key information from contracts or case law.
  • Legal Research: Assisting with queries related to legal statutes, precedents, and regulations.
  • Legal Question Answering: Providing informed responses to legal questions based on its specialized training.

Users should be aware that while fine-tuned for legal contexts, the model's performance should be evaluated for specific use cases to ensure accuracy and compliance.

Finetunes
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