protocolsyncllc/medgap-gemma-4-12b

TEXT GENERATIONPricing:Input $1.2 / Cached $0.24 / Output $4.8Concurrent Unit Cost:1Model Size:12BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 3, 2026License:llama3Architecture:Transformer Featherless Exclusive Cold

The protocolsyncllc/medgap-gemma-4-12b is a 12 billion parameter language model fine-tuned from Google's Gemma 4 12B-it. This model specializes in processing and understanding FDA warning letters specifically for medical devices. It was fine-tuned using a LoRA technique on a dataset of medical device-related FDA warning letters, making it highly effective for regulatory compliance and analysis in the medical device sector.

Loading preview...

Model Overview

The protocolsyncllc/medgap-gemma-4-12b is a specialized large language model, fine-tuned from the Google Gemma 4 12B-it base model. It has 12 billion parameters and a context length of 32768 tokens. The primary focus of this model is the analysis and understanding of FDA warning letters related to medical devices.

Key Capabilities

  • Specialized Domain Knowledge: Fine-tuned specifically on a dataset of FDA warning letters for medical devices, providing deep expertise in this regulatory area.
  • Fine-tuning Technique: Utilizes LoRA (Low-Rank Adaptation) for efficient and effective adaptation to the target domain.
  • Base Model: Built upon Google's Gemma 4 12B-it, inheriting its strong foundational language understanding capabilities.

Good For

  • Regulatory Compliance: Analyzing and interpreting FDA warning letters for medical device companies.
  • Medical Device Industry: Applications requiring an understanding of regulatory communications and compliance issues specific to medical devices.
  • Information Extraction: Extracting key information, issues, and requirements from FDA warning letters.

Finetunes
1 models