HYU-NLP-EVAL/qwen3-4b-rar-medicine-static-r0-matched-dense-seed11-step-003

TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:4BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Oct 1, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

HYU-NLP-EVAL/qwen3-4b-rar-medicine-static-r0-matched-dense-seed11-step-003 is a 4 billion parameter Qwen3 model developed by HYU-NLP-EVAL, specifically a RaR-Medicine static R0 matched dense checkpoint. This model is designed for research use only and is provided in BF16 format for inference. Its primary differentiator is its specialized fine-tuning for medical applications, making it suitable for tasks within the medical domain.

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Overview

This model, HYU-NLP-EVAL/qwen3-4b-rar-medicine-static-r0-matched-dense-seed11-step-003, is a specialized 4 billion parameter variant of the Qwen3 architecture. It represents a RaR-Medicine static R0 matched dense checkpoint, specifically from the run phase1-static-r0-medicine-qwen3-4b-matched-dense-20260928-seed11. The model is provided in BF16 format, optimized for efficient inference.

Key Capabilities

  • Medical Domain Specialization: Fine-tuned for applications within the medical field, indicating potential for tasks requiring medical knowledge.
  • Efficient Inference: Available in BF16 format, which is suitable for deployment where computational efficiency is important.

Good for

  • Medical Research: Ideal for researchers exploring language models in healthcare and medicine.
  • Domain-Specific Applications: Suitable for experimental use in medical text analysis, information extraction, or question-answering within a medical context.

Note: This model is intended for research use only.

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