L1nus/qwen3-4b-pubmedqa-thinking-exclude-default-5000

TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kTool Calling:SupportedPublished:May 27, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

L1nus/qwen3-4b-pubmedqa-thinking-exclude-default-5000 is a 4 billion parameter Qwen3 model developed by L1nus, fine-tuned from unsloth/Qwen3-4B. This model was trained with Unsloth for accelerated performance, offering a 32768 token context length. It is designed for specific applications, likely related to PubMed QA and 'thinking' tasks, given its specialized fine-tuning.

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Model Overview

L1nus/qwen3-4b-pubmedqa-thinking-exclude-default-5000 is a 4 billion parameter language model, fine-tuned by L1nus from the base unsloth/Qwen3-4B architecture. This model leverages the Unsloth framework, which enabled a 2x faster training process. It operates with a substantial context length of 32768 tokens, making it suitable for processing longer inputs.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/Qwen3-4B.
  • Parameter Count: 4 billion parameters.
  • Training Efficiency: Utilizes Unsloth for accelerated training, achieving 2x faster speeds.
  • Context Length: Supports a 32768 token context window.
  • License: Distributed under the Apache-2.0 license.

Potential Use Cases

Given its specific naming convention, including "pubmedqa" and "thinking," this model is likely specialized for:

  • Biomedical Question Answering: Particularly within the domain of PubMed, suggesting expertise in medical literature comprehension.
  • Reasoning Tasks: The "thinking" aspect implies an optimization for tasks requiring logical inference or complex problem-solving.

This model is a specialized variant of the Qwen3 series, tailored for specific domain-centric applications.

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