syaefur/pgabl-wafa-legal-assistant-sft-exp1

TEXT GENERATIONConcurrent Unit Cost:1Model Size:1.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 11, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The syaefur/pgabl-wafa-legal-assistant-sft-exp1 is a 1.5 billion parameter Qwen2.5-Instruct model, developed by syaefur, and fine-tuned for legal assistance tasks. It was trained using Unsloth and Huggingface's TRL library, enabling faster fine-tuning. This model is designed to provide specialized support for legal queries and information processing, leveraging its 32768 token context length.

Loading preview...

Model Overview

The syaefur/pgabl-wafa-legal-assistant-sft-exp1 is a 1.5 billion parameter Qwen2.5-Instruct model, developed by syaefur. It has been specifically fine-tuned to function as a legal assistant, leveraging its substantial 32768 token context length for processing extensive legal documents and queries.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/Qwen2.5-1.5B-Instruct-bnb-4bit.
  • Training Efficiency: The model was fine-tuned with Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
  • Parameter Count: Features 1.5 billion parameters, offering a balance between performance and computational efficiency.
  • Context Length: Supports a 32768 token context window, suitable for handling detailed and lengthy legal texts.

Use Cases

This model is particularly well-suited for applications requiring specialized legal knowledge and assistance. Potential use cases include:

  • Answering legal questions.
  • Summarizing legal documents.
  • Assisting with legal research.
  • Drafting legal-related content.

Finetunes
1 models