HYU-NLP-EVAL/qwen3-4b-rar-medicine-onlinerubrics-dense-seed11-step-020

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-onlinerubrics-dense-seed11-step-020 is a 4 billion parameter Qwen3-based model, specifically a dense checkpoint from the RaR-Medicine OnlineRubrics project. This model is designed for research use, focusing on applications within the medical domain. It is derived from the "phase1-online-rubrics-medicine-full-dense-20260919-seed11" run and includes original veRL checkpoint files for model parameters.

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Overview

This model, HYU-NLP-EVAL/qwen3-4b-rar-medicine-onlinerubrics-dense-seed11-step-020, is a 4 billion parameter variant based on the Qwen3 architecture. It represents a dense checkpoint from the RaR-Medicine OnlineRubrics project, specifically from the "phase1-online-rubrics-medicine-full-dense-20260919-seed11" run. The model is provided in BF16 format for inference, with original veRL checkpoint files (model parameters only) also included.

Key Capabilities

  • Medical Domain Focus: Optimized for tasks within the medical field, stemming from the RaR-Medicine OnlineRubrics project.
  • Dense Checkpoint: Represents a specific, dense checkpoint from its training run, indicating a particular stage of optimization.
  • Research Use: Primarily intended for research and development purposes.

Good for

  • Medical NLP Research: Ideal for researchers exploring language models in medical contexts.
  • Experimentation: Suitable for experimenting with specific checkpoints from the RaR-Medicine OnlineRubrics project.
  • Fine-tuning: Can serve as a base for further fine-tuning on specialized medical datasets.

Finetunes
1 models