ishikaa/acquisition_student_AS_format_medmcqa_qwen14b

TEXT GENERATIONPricing:Input $0.431 / Cached $0.0862 / Output $1.12Concurrent Unit Cost:1Model Size:14.8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 7, 2026Architecture:Transformer Featherless Exclusive Cold

The ishikaa/acquisition_student_AS_format_medmcqa_qwen14b model is a 14.8 billion parameter language model developed by ishikaa. This model is designed for specific acquisition student format tasks related to MedMCQA, indicating a specialized fine-tuning for medical question-answering in a particular educational context. Its primary strength lies in processing and generating responses tailored to the MedMCQA dataset's structure and content.

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Model Overview

The ishikaa/acquisition_student_AS_format_medmcqa_qwen14b is a 14.8 billion parameter language model. It has been developed by ishikaa with a focus on specific tasks related to the MedMCQA dataset, likely involving a specialized 'acquisition student' format. The model's architecture and training details are not explicitly provided in the current model card, but its naming suggests a fine-tuned application within the medical question-answering domain.

Key Characteristics

  • Parameter Count: 14.8 billion parameters.
  • Context Length: Supports a context length of 32768 tokens.
  • Specialization: Appears to be fine-tuned for tasks related to the MedMCQA dataset, potentially for educational or assessment purposes in a medical context.

Intended Use Cases

Given its specialized naming, this model is likely intended for:

  • Medical Question Answering: Processing and generating answers for questions within the MedMCQA dataset.
  • Educational Applications: Assisting students or educators with content related to medical knowledge in a structured format.

Further details on its specific capabilities, training data, and performance metrics are currently marked as "More Information Needed" in the model card.