Kadabra/Gemma4-e2b-SFT

VISIONConcurrent Unit Cost:1Model Size:5.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 30, 2026Architecture:Transformer Featherless Exclusive Cold

Kadabra/Gemma4-e2b-SFT is a 5.1 billion parameter instruction-tuned language model, fine-tuned and converted to GGUF format using Unsloth. This model is optimized for efficient deployment and inference, leveraging Unsloth's accelerated training and conversion process. It is designed for general text-based applications, offering a balance of performance and resource efficiency.

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Overview

Kadabra/Gemma4-e2b-SFT is a 5.1 billion parameter instruction-tuned language model, specifically designed for efficient deployment and inference. This model has been fine-tuned and converted into the GGUF format, a process significantly accelerated by the Unsloth framework. Unsloth's optimization allows for faster training and conversion, making this model particularly suitable for environments where resource efficiency and quick deployment are critical.

Key Capabilities

  • Efficient Inference: Provided in GGUF format, enabling optimized performance on various hardware.
  • Instruction-Tuned: Designed to follow instructions effectively for a wide range of text-based tasks.
  • Accelerated Development: Benefits from Unsloth's 2x faster training and conversion process.

Available Formats

The model is available in several quantized GGUF formats, including Q6_K, Q3_K_M, Q2_K_L, Q8_0, Q5_K_M, Q4_K_M, and BF16-mmproj, offering flexibility for different performance and memory requirements.

Good For

  • Applications requiring a capable instruction-following model with a moderate parameter count.
  • Deployments where efficient resource utilization and fast inference are priorities.
  • Developers looking for models optimized with Unsloth for ease of use and performance.

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