gmongaras/Wizard_7B_Squad_v2
TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kLicense:openrailArchitecture:Transformer Open Weights Cold
gmongaras/Wizard_7B_Squad_v2 is a 7 billion parameter language model based on the WizardLM architecture, fine-tuned specifically on the SQuAD dataset. This model is optimized for question answering tasks, leveraging its training on a comprehensive dataset of questions and corresponding answers. Its primary strength lies in accurately extracting information and generating precise responses to queries.
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Model Overview
gmongaras/Wizard_7B_Squad_v2 is a specialized language model built upon the WizardLM-7B architecture. Its key differentiator is its fine-tuning on the SQuAD (Stanford Question Answering Dataset), which focuses on reading comprehension and question answering.
Key Capabilities
- Question Answering: Excels at understanding questions and extracting relevant answers from provided contexts, a direct result of its SQuAD training.
- Information Extraction: Designed to pinpoint and retrieve specific pieces of information in response to queries.
Training Details
This model underwent a focused training regimen:
- Base Model: Derived from TheBloke's WizardLM-7B-HF.
- Dataset: Fine-tuned exclusively on the SQuAD dataset.
- Training Steps: Trained for 6000 steps with a batch size of 8 and 2 accumulation steps, indicating a deliberate optimization for its target task.