nityaak/qwen3-8b-stance-matrix-semeval-ezstance-qlora
TEXT GENERATIONPricing:Input $0.468 / Output $1.82Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 11, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The nityaak/qwen3-8b-stance-matrix-semeval-ezstance-qlora is an 8 billion parameter Qwen3 model, developed by nityaak, fine-tuned for specific tasks. It was trained using Unsloth and Huggingface's TRL library, enabling faster training. This model is optimized for applications requiring a Qwen3 architecture with efficient training methods.
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Model Overview
This model, nityaak/qwen3-8b-stance-matrix-semeval-ezstance-qlora, is an 8 billion parameter Qwen3-based language model developed by nityaak. It was fine-tuned from unsloth/Qwen3-8B-unsloth-bnb-4bit and utilizes the QLoRA technique for efficient training.
Key Capabilities
- Efficient Training: The model was trained 2x faster using Unsloth and Huggingface's TRL library, indicating optimized resource usage during its development.
- Qwen3 Architecture: Built upon the Qwen3 foundation, it inherits the general capabilities of this model family.
- Specific Fine-tuning: The model name suggests fine-tuning for "stance-matrix-semeval-ezstance" tasks, implying specialization in areas like stance detection or semantic evaluation, though specific performance metrics are not provided in the README.
Good For
- Developers looking for a Qwen3-8B model that has undergone efficient QLoRA fine-tuning.
- Applications that might benefit from a model potentially specialized in tasks related to stance detection or semantic analysis, as indicated by its fine-tuning objective.