Tristepin/udk-ue3-qw34b-v2
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Mar 12, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
Tristepin/udk-ue3-qw34b-v2 is a 4 billion parameter language model developed by Tristepin, fine-tuned from Jackrong/Qwen3-4B-2507-Claude-4.6-Opus-Reasoning-Distilled. This model was trained using Unsloth and Huggingface's TRL library, achieving a 2x speedup during the fine-tuning process. It is designed for general language tasks, leveraging its Qwen3 base and efficient training methodology.
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Overview
Tristepin/udk-ue3-qw34b-v2 is a 4 billion parameter language model developed by Tristepin. It is a fine-tuned version of the Jackrong/Qwen3-4B-2507-Claude-4.6-Opus-Reasoning-Distilled model, leveraging the Qwen3 architecture.
Key Capabilities
- Efficient Fine-tuning: This model was fine-tuned with a 2x speed improvement using Unsloth and Huggingface's TRL library, indicating an optimized training process.
- Qwen3 Base: Built upon the Qwen3 architecture, it inherits the foundational capabilities of that model family.
Good for
- General Language Tasks: Suitable for a wide range of natural language processing applications due to its Qwen3 base.
- Resource-Efficient Deployment: The 4 billion parameter size makes it a good candidate for applications where computational resources are a consideration, especially given its optimized fine-tuning.
- Experimentation with Efficient Training: Developers interested in models trained with Unsloth for speed and efficiency may find this model particularly useful.