mervinpraison/praisonai-gemma-4-E4B-tamil
VISIONConcurrent Unit Cost:1Model Size:7.9BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 22, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Cold
The mervinpraison/praisonai-gemma-4-E4B-tamil is a 7.9 billion parameter language model, finetuned by mervinpraison from the unsloth/gemma-4-e4b-it-unsloth-bnb-4bit base model. It was trained using Unsloth and Huggingface's TRL library, enabling faster fine-tuning. This model is optimized for tasks requiring a large context window of 32768 tokens and is specifically adapted for the Tamil language.
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Model Overview
The mervinpraison/praisonai-gemma-4-E4B-tamil is a 7.9 billion parameter language model, developed by mervinpraison. It is a finetuned version of the unsloth/gemma-4-e4b-it-unsloth-bnb-4bit model, leveraging the Gemma 4 architecture.
Key Characteristics
- Base Model: Finetuned from
unsloth/gemma-4-e4b-it-unsloth-bnb-4bit. - Parameter Count: Features 7.9 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a substantial context window of 32768 tokens, suitable for processing longer texts and complex queries.
- Training Efficiency: The model was fine-tuned with significantly improved speed using the Unsloth library in conjunction with Huggingface's TRL library.
- Language Focus: Specifically adapted for the Tamil language, making it suitable for applications requiring strong performance in this linguistic domain.
Use Cases
This model is particularly well-suited for applications that require:
- Processing and generating text in Tamil.
- Tasks benefiting from a large context window, such as summarization of long documents or complex question answering.
- Deployment in environments where efficient fine-tuning and inference are critical, thanks to its Unsloth-optimized training.