Softsasi/factchecker-qwen-merged
TEXT GENERATIONConcurrency Cost:1Model Size:1.5BQuant:BF16Ctx Length:32kTool Calling:SupportedPublished:Jun 11, 2026Architecture:Transformer Cold
Softsasi/factchecker-qwen-merged is a 1.5 billion parameter language model based on the Qwen2.5 architecture, fine-tuned for fact-checking applications. Utilizing unsloth for efficient training, this model is designed to assist in verifying information. It supports a context length of 32768 tokens, making it suitable for processing longer texts in fact-checking tasks.
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Model Overview
Softsasi/factchecker-qwen-merged is a 1.5 billion parameter language model built upon the Qwen2.5-Instruct architecture. It has been fine-tuned using the Unsloth library for efficient training and inference, specifically targeting fact-checking applications.
Key Capabilities
- Fact-Checking Focus: Optimized for tasks related to verifying information and identifying inaccuracies.
- Efficient Performance: Leverages Unsloth for reduced memory usage and faster fine-tuning and inference speeds.
- Extended Context: Supports a substantial context window of 32768 tokens, enabling the analysis of longer documents or conversations for fact verification.
- Qwen2.5 Base: Benefits from the strong foundational capabilities of the Qwen2.5 series, known for its general language understanding.
Good For
- Information Verification: Ideal for developers building systems that require automated or semi-automated fact-checking.
- Content Moderation: Can be integrated into tools for identifying potentially misleading or false information in user-generated content.
- Research Assistance: Useful for quickly sifting through large amounts of text to cross-reference facts and claims.
This model is released under the Apache-2.0 license and primarily supports the English language.