leeccNLPLAB/unsloth_Qwen3-4B-unsloth-bnb-4bit-BookSQL

TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kTool Calling:SupportedPublished:May 21, 2025License:apache-2.0Architecture:Transformer Open Weights Cold

The leeccNLPLAB/unsloth_Qwen3-4B-unsloth-bnb-4bit-BookSQL is a 4 billion parameter Qwen3-based language model developed by leeccNLPLAB. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is optimized for specific tasks, likely related to SQL or book-related data, given its specialized fine-tuning.

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Model Overview

The leeccNLPLAB/unsloth_Qwen3-4B-unsloth-bnb-4bit-BookSQL is a 4 billion parameter language model based on the Qwen3 architecture. Developed by leeccNLPLAB, this model was fine-tuned using a combination of Unsloth and Huggingface's TRL library, which significantly accelerated its training process by 2x.

Key Characteristics

  • Base Model: Qwen3-4B
  • Parameter Count: 4 billion
  • Training Optimization: Utilizes Unsloth for 2x faster fine-tuning.
  • Fine-tuning Frameworks: Unsloth and Huggingface's TRL library.
  • Context Length: Supports a substantial context of 32,768 tokens.

Potential Use Cases

Given its specialized naming convention (BookSQL), this model is likely tailored for applications involving:

  • SQL-related tasks: Such as natural language to SQL conversion, SQL query generation, or database interaction.
  • Book-related data processing: Including summarization, question answering, or information extraction from textual book content.

This model offers a performant and efficiently trained solution for developers working with specific data domains that align with its fine-tuning focus.

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