kiran-varma/gemma-4-E4B-it-FT
The kiran-varma/gemma-4-E4B-it-FT is a 5.1 billion parameter instruction-tuned language model developed by kiran-varma. This model is finetuned from unsloth/gemma-4-e2b-it-unsloth-bnb-4bit and was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language generation tasks, leveraging its optimized training process for efficiency.
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Model Overview
The kiran-varma/gemma-4-E4B-it-FT is a 5.1 billion parameter instruction-tuned language model developed by kiran-varma. It is finetuned from the unsloth/gemma-4-e2b-it-unsloth-bnb-4bit base model.
Key Characteristics
- Architecture: Based on the Gemma-4 family.
- Parameter Count: 5.1 billion parameters.
- Training Efficiency: This model was trained with a focus on efficiency, utilizing Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- Context Length: Supports a context length of 32768 tokens.
Use Cases
This model is suitable for various instruction-following tasks, benefiting from its optimized training. Its efficient development process suggests it could be a good candidate for applications where rapid iteration or resource-conscious deployment is important.