HYU-NLP-EVAL/qwen3-4b-rar-medicine-static-r0-matched-dense-seed11-step-007

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-007 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 characteristic is its specialized training within the medical domain, indicated by 'RaR-Medicine', making it suitable for tasks requiring medical knowledge.

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Overview

This model, HYU-NLP-EVAL/qwen3-4b-rar-medicine-static-r0-matched-dense-seed11-step-007, is a specialized 4 billion parameter variant of the Qwen3 architecture. It represents a RaR-Medicine static R0 matched dense checkpoint, specifically from 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: Tuned for tasks within the medical field, indicated by its 'RaR-Medicine' designation.
  • Efficient Inference: Available in BF16 format, suitable for deployment where computational efficiency is important.
  • Research-Oriented: Primarily intended for research purposes, allowing for exploration and development in medical NLP applications.

Good for

  • Researchers working on medical language understanding and generation tasks.
  • Experiments requiring a specialized Qwen3 model with a focus on medicine.
  • Evaluating performance of language models in specific medical contexts.

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