armand0e/Gemma-4-E4B-it-Fable-Distill

VISIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.9BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 21, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

armand0e/Gemma-4-E4B-it-Fable-Distill is a 7.9 billion parameter instruction-tuned causal language model developed by armand0e. This model is finetuned from unsloth/gemma-4-E4B-it and was trained using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general instruction-following tasks, leveraging its efficient training methodology.

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Model Overview

armand0e/Gemma-4-E4B-it-Fable-Distill is an instruction-tuned language model with 7.9 billion parameters, developed by armand0e. It is based on the unsloth/gemma-4-E4B-it model and utilizes the Unsloth library in conjunction with Huggingface's TRL library for its finetuning process. A key characteristic of this model's development is its optimized training, which was reportedly twice as fast due to the use of Unsloth.

Key Characteristics

  • Parameter Count: 7.9 billion parameters.
  • Base Model: Finetuned from unsloth/gemma-4-E4B-it.
  • Training Efficiency: Leverages Unsloth for significantly faster training times.
  • Training Libraries: Developed using Unsloth and Huggingface's TRL library.

Intended Use Cases

This model is suitable for a variety of instruction-following tasks, benefiting from its efficient finetuning. Its development methodology suggests a focus on practical application and rapid iteration, making it a candidate for projects where quick deployment and performance are valued.

Finetunes
2 models