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Few Shot Learning On Medconceptsqa

Metrics

Accuracy

Results

Performance results of various models on this benchmark

Model Name
Accuracy
Paper TitleRepository
gpt-4-0125-preview61.911GPT-4 Technical Report-
epfl-llm/meditron-70b25.262MEDITRON-70B: Scaling Medical Pretraining for Large Language Models-
dmis-lab/biobert-v1.125.458BioBERT: a pre-trained biomedical language representation model for biomedical text mining-
johnsnowlabs/JSL-MedMNX-7B25.627MedConceptsQA: Open Source Medical Concepts QA Benchmark-
dmis-lab/meerkat-7b-v1.024.942Small Language Models Learn Enhanced Reasoning Skills from Medical Textbooks-
HuggingFaceH4/zephyr-7b-beta25.058Zephyr: Direct Distillation of LM Alignment-
yikuan8/Clinical-Longformer25.547Clinical-Longformer and Clinical-BigBird: Transformers for long clinical sequences-
gpt-3.5-turbo41.476Language Models are Few-Shot Learners-
meta-llama/Meta-Llama-3-8B-Instruct25.653LLaMA: Open and Efficient Foundation Language Models-
BioMistral/BioMistral-7B-DARE25.058BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains-
epfl-llm/meditron-7b23.787MEDITRON-70B: Scaling Medical Pretraining for Large Language Models-
PharMolix/BioMedGPT-LM-7B24.924BioMedGPT: Open Multimodal Generative Pre-trained Transformer for BioMedicine-
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Few Shot Learning On Medconceptsqa | SOTA | HyperAI