didula-wso2/gemma4_sft-ballerina_klge42sft_16bit_vllm

VISIONConcurrency Cost:1Model Size:7.9BQuant:FP8Ctx Length:32kTool Calling:SupportedPublished:Jun 16, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

The didula-wso2/gemma4_sft-ballerina_klge42sft_16bit_vllm is a 7.9 billion parameter Gemma 4-E4B-it model, fine-tuned by didula-wso2. This model was trained using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general language tasks, leveraging its 32768 token context length for processing extensive inputs.

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Model Overview

The didula-wso2/gemma4_sft-ballerina_klge42sft_16bit_vllm is a fine-tuned language model based on the Gemma 4-E4B-it architecture, developed by didula-wso2. This model features 7.9 billion parameters and supports a substantial context length of 32768 tokens, making it suitable for tasks requiring extensive input processing.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/gemma-4-E4B-it.
  • Training Efficiency: Utilizes Unsloth and Huggingface's TRL library for accelerated training, reportedly achieving 2x faster training speeds.
  • Parameter Count: Contains 7.9 billion parameters.
  • Context Length: Supports a 32768 token context window.

Potential Use Cases

Given its foundation in the Gemma 4-E4B-it model and its significant context length, this model is well-suited for:

  • General text generation and understanding tasks.
  • Applications requiring processing of long documents or conversations.
  • Tasks benefiting from a model fine-tuned with efficient methods.