mouaaddraa/NutriCare-Al-Qwen3.5-FT

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:0.8BQuant:BF16Ctx Length:32kPublished:May 11, 2026License:apache-2.0Architecture:Transformer Open Weights Warm

NutriCare-Al-Qwen3.5-FT is a 0.8 billion parameter Qwen3 model developed by mouaaddraa, fine-tuned using Unsloth and Huggingface's TRL library. This model was trained significantly faster, leveraging optimized techniques for efficient fine-tuning. It is designed for applications requiring a compact yet capable language model, benefiting from its accelerated training process.

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Overview

NutriCare-Al-Qwen3.5-FT is a compact 0.8 billion parameter language model based on the Qwen3 architecture, developed by mouaaddraa. This model was fine-tuned using a specialized process involving Unsloth and Huggingface's TRL library, which enabled a 2x faster training time compared to standard methods. The accelerated training makes it an efficient option for developers looking to deploy a capable model quickly.

Key Capabilities

  • Efficient Fine-tuning: Leverages Unsloth for significantly faster training, reducing development cycles.
  • Compact Size: At 0.8 billion parameters, it offers a balance between performance and resource efficiency.
  • Qwen3 Architecture: Built upon the robust Qwen3 foundation, providing a strong base for various NLP tasks.

Good For

  • Applications requiring a lightweight and fast-to-deploy language model.
  • Scenarios where rapid iteration and fine-tuning are crucial.
  • Developers seeking an efficient Qwen3-based model for specific tasks.