Hothaifa/HEQ-Agent-1.0.0

Hugging Face
VISIONConcurrency Cost:2Model Size:31BQuant:FP8Ctx Length:32kTool Calling:SupportedPublished:Jun 3, 2026License:apache-2.0Architecture:Transformer Open Weights Warm

Hothaifa/HEQ-Agent-1.0.0 is a 31 billion parameter Gemma4-based model developed by Hothaifa, fine-tuned using Unsloth and Huggingface's TRL library. This model is optimized for efficient training, having been trained 2x faster. It is designed for general-purpose agentic tasks, leveraging its efficient fine-tuning process.

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Model Overview

Hothaifa/HEQ-Agent-1.0.0 is a 31 billion parameter model developed by Hothaifa. It is based on the Gemma4 architecture and has been fine-tuned using the Unsloth library in conjunction with Huggingface's TRL library. This specific fine-tuning approach enabled the model to be trained 2x faster than conventional methods.

Key Characteristics

  • Architecture: Gemma4 base model.
  • Parameter Count: 31 billion parameters.
  • Efficient Training: Utilizes Unsloth for significantly accelerated fine-tuning (2x faster).
  • Context Length: Supports a context length of 32768 tokens.

Potential Use Cases

Given its efficient training and substantial parameter count, Hothaifa/HEQ-Agent-1.0.0 is suitable for applications requiring a capable language model with a focus on agentic behaviors. Its optimized training process suggests it could be a strong candidate for scenarios where rapid iteration and deployment of fine-tuned models are beneficial.