alvian-metalit/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:Jul 26, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The alvian-metalit/qwen2.5-3b-legal-id-sft is a 3.1 billion parameter Qwen2.5 model developed by alvian-metalit, fine-tuned from unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is specifically optimized for legal identification tasks, leveraging its 32768 token context length for processing extensive legal documents.

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Model Overview

The alvian-metalit/qwen2.5-3b-legal-id-sft is a 3.1 billion parameter language model developed by alvian-metalit. It is fine-tuned from the unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit base model, leveraging the Qwen2.5 architecture.

Key Characteristics

  • Efficient Training: This model was trained with Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
  • Base Model: Finetuned from unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit, indicating a foundation in instruction-tuned Qwen2.5 models.
  • Context Length: Features a substantial context window of 32768 tokens, suitable for processing longer inputs.

Intended Use

This model is specifically fine-tuned for legal identification tasks. Its training methodology and base model suggest capabilities in understanding and processing instructions, which, combined with its large context window, make it suitable for applications requiring detailed analysis of legal texts for identification purposes.

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