hnda/qwen3-4b-alf-sft-merged-v2
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Feb 16, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The hnda/qwen3-4b-alf-sft-merged-v2 is a 4 billion parameter Qwen3-based language model developed by hnda, fine-tuned from hnda/qwen3-4b-alf-sft-merged. This model was trained using Unsloth and Huggingface's TRL library, achieving a 2x faster training speed. It is designed for general language understanding and generation tasks, offering efficient performance for its size.
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Overview
hnda/qwen3-4b-alf-sft-merged-v2 is a 4 billion parameter language model developed by hnda, building upon the Qwen3 architecture. This model is a fine-tuned version of hnda/qwen3-4b-alf-sft-merged.
Key Capabilities
- Efficient Training: Achieved 2x faster training speed by leveraging Unsloth and Huggingface's TRL library.
- Qwen3 Architecture: Benefits from the robust base architecture of Qwen3 models.
- General Purpose: Suitable for a wide range of natural language processing tasks.
Good for
- Applications requiring a compact yet capable language model.
- Scenarios where training efficiency is a critical factor.
- Developers looking for a Qwen3-based model with optimized fine-tuning.