symrizals/qwen2.5-3b-legal-id-sft

TEXT GENERATIONPricing:Input $0.32 / Cached $0.064 / Output $1.6Concurrent Unit Cost:1Model Size:3.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 27, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The symrizals/qwen2.5-3b-legal-id-sft is a 3.1 billion parameter Qwen2.5 model, developed by symrizals, and fine-tuned for specific legal identification tasks. This model was trained using Unsloth and Huggingface's TRL library, enabling faster fine-tuning. It is optimized for applications requiring specialized legal domain understanding, leveraging its Qwen2.5 architecture and 32768 token context length.

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Model Overview

The symrizals/qwen2.5-3b-legal-id-sft is a 3.1 billion parameter language model based on the Qwen2.5 architecture. Developed by symrizals, this model has been specifically fine-tuned for tasks related to legal identification.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/Qwen2.5-3B-bnb-4bit.
  • Training Efficiency: The fine-tuning process was accelerated using Unsloth and Huggingface's TRL library, resulting in a 2x faster training time.
  • Context Length: Features a substantial context window of 32768 tokens, beneficial for processing longer legal documents.

Intended Use Cases

This model is particularly suited for applications within the legal domain that require specialized understanding and identification capabilities. Its fine-tuning suggests an optimization for tasks where precise recognition and processing of legal information are critical.

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