ermiaazarkhalili/Qwen3.5-9B-SFT-Fable5-Glint

VISIONConcurrent Unit Cost:1Model Size:9BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jun 27, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The ermiaazarkhalili/Qwen3.5-9B-SFT-Fable5-Glint is a 9 billion parameter Qwen3.5 model, fine-tuned by ermiaazarkhalili. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster fine-tuning. It is designed for general language tasks, leveraging its Qwen3.5 architecture and efficient training methodology.

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Model Overview

This model, ermiaazarkhalili/Qwen3.5-9B-SFT-Fable5-Glint, is a 9 billion parameter language model based on the Qwen3.5 architecture. It was developed by ermiaazarkhalili and is licensed under Apache-2.0.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/Qwen3.5-9B.
  • Efficient Training: The model was fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
  • Parameter Count: Features 9 billion parameters, offering a balance between performance and computational efficiency.
  • Context Length: Supports a context length of 32768 tokens.

Potential Use Cases

Given its Qwen3.5 base and efficient fine-tuning, this model is suitable for a variety of general-purpose language generation and understanding tasks. Its optimized training suggests it could be a good candidate for applications where rapid deployment of fine-tuned models is beneficial.

Finetunes
2 models