abzoo/gemma4-e2b-egyptian-id-ocr

VISIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:5.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 30, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The abzoo/gemma4-e2b-egyptian-id-ocr model is a 5.1 billion parameter language model developed by abzoo, finetuned from unsloth/gemma-4-E2B-it. It was trained using Unsloth and Huggingface's TRL library, enabling 2x faster finetuning. This model is specifically optimized for Egyptian ID OCR tasks, leveraging its 32768 token context length for processing detailed document information.

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Model Overview

The abzoo/gemma4-e2b-egyptian-id-ocr is a 5.1 billion parameter language model developed by abzoo. It is finetuned from the unsloth/gemma-4-E2B-it base model, utilizing the Unsloth library and Huggingface's TRL for efficient training. This approach allowed for a 2x speedup in the finetuning process.

Key Characteristics

  • Parameter Count: 5.1 billion parameters, offering a balance between performance and computational efficiency.
  • Context Length: Features a substantial 32768 token context window, suitable for processing lengthy inputs.
  • Training Efficiency: Leverages Unsloth for accelerated finetuning, making it a practical choice for specialized applications.

Primary Use Case

This model is specifically designed and optimized for Egyptian ID OCR (Optical Character Recognition) tasks. Its finetuning and architecture make it well-suited for accurately extracting and interpreting information from Egyptian identification documents. Developers looking for a specialized model for document processing in this domain will find this model particularly useful due to its targeted optimization.

Finetunes
2 models