johnsnowlabs/JSL-MedPhi2-2.7B
TEXT GENERATIONPricing:Input $0.32 / Cached $0.064 / Output $1.6Concurrent Unit Cost:1Model Size:3BQuant:BF16Context Size:2kPublished:Apr 30, 2024License:cc-by-nc-nd-4.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Warm
JSL-MedPhi2-2.7B is a 2.7 billion parameter language model developed by John Snow Labs, specifically fine-tuned for medical question answering and clinical knowledge tasks. This model demonstrates strong performance across various medical benchmarks, including MMLU subtasks like clinical knowledge and medical genetics. It is optimized for applications requiring accurate and contextually relevant responses within the healthcare domain.
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JSL-MedPhi2-2.7B: A Medical Language Model
JSL-MedPhi2-2.7B is a 2.7 billion parameter language model developed by John Snow Labs, specifically designed and fine-tuned for medical and clinical applications. This model leverages its specialized training to provide relevant and accurate responses within the healthcare domain.
Key Capabilities
- Medical Question Answering: Achieves notable scores on medical question-answering datasets such as MedMCQA and MedQA.
- Clinical Knowledge: Demonstrates proficiency in MMLU subtasks related to clinical knowledge (0.6340 acc), medical genetics (0.6300 acc), and college medicine (0.5665 acc).
- Specialized Domain Understanding: Optimized for understanding and generating text within the medical field, making it suitable for tasks requiring deep domain-specific knowledge.
Good For
- Healthcare AI Applications: Ideal for integrating into systems that require robust medical language understanding.
- Clinical Decision Support: Can assist in tasks requiring access to or generation of clinical information.
- Medical Research: Useful for processing and analyzing medical literature or data.