ajujohn8/gemma-e4b-it-modeltrainingCFT-SFT
VISIONConcurrent Unit Cost:1Model Size:7.9BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 7, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The ajujohn8/gemma-e4b-it-modeltrainingCFT-SFT is a 7.9 billion parameter Gemma-4 based instruction-tuned language model developed by ajujohn8. This model was fine-tuned using Unsloth and Hugging Face's TRL library, resulting in a 2x faster training process. It is designed for general instruction-following tasks, leveraging its efficient training methodology.
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Model Overview
The ajujohn8/gemma-e4b-it-modeltrainingCFT-SFT is an instruction-tuned language model based on the Gemma-4 architecture, featuring 7.9 billion parameters and a 32K context length. Developed by ajujohn8, this model was fine-tuned from ajujohn8/gemma-4-e4b-it-unsloth-bnb-4bit-aj.
Key Capabilities
- Efficient Fine-tuning: This model was trained significantly faster, achieving a 2x speedup, by utilizing the Unsloth library in conjunction with Hugging Face's TRL library.
- Instruction Following: As an instruction-tuned model, it is designed to understand and execute commands or prompts effectively.
Good For
- Applications requiring a Gemma-4 based model with optimized training.
- General instruction-following tasks where efficient fine-tuning is a priority.