nityaak/qwen3-8b-stance-matrix-semeval-mtcsd-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-mtcsd-qlora is an 8 billion parameter Qwen3 model developed by nityaak. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is specifically optimized for tasks related to stance detection, likely within the SemEval-MTCSD context. Its primary strength lies in its specialized fine-tuning for specific natural language understanding challenges.
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Model Overview
The nityaak/qwen3-8b-stance-matrix-semeval-mtcsd-qlora is an 8 billion parameter Qwen3 model developed by nityaak. This model has been fine-tuned from the unsloth/Qwen3-8B-unsloth-bnb-4bit base model.
Key Capabilities
- Efficient Fine-tuning: The model was fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- Specialized for Stance Detection: The model's name, including "stance-matrix-semeval-mtcsd-qlora," indicates its specific optimization for stance detection tasks, likely within the context of SemEval's Multi-Target Stance Detection (MTCSD) challenges.
Good For
- Applications requiring a specialized Qwen3 model for stance detection.
- Research and development in natural language understanding, particularly for identifying opinions and stances towards specific targets.
- Leveraging the efficiency benefits of Unsloth for faster deployment and iteration of fine-tuned models.