hadasor/Qwen2.5-14B-Instruct-Pruned2
TEXT GENERATIONConcurrent Unit Cost:1Model Size:14.8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jun 25, 2026Architecture:Transformer Featherless Exclusive Cold
The hadasor/Qwen2.5-14B-Instruct-Pruned2 is a 14.8 billion parameter instruction-tuned language model based on the Qwen2.5 architecture. This model is a pruned version, indicating optimization for efficiency while retaining core capabilities. It is designed for general-purpose conversational AI and instruction following tasks, leveraging its substantial parameter count for robust language understanding and generation.
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Model Overview
The hadasor/Qwen2.5-14B-Instruct-Pruned2 is a 14.8 billion parameter instruction-tuned language model. It is built upon the Qwen2.5 architecture and has undergone pruning, suggesting an optimization process to reduce model size or computational requirements while aiming to maintain performance.
Key Characteristics
- Parameter Count: 14.8 billion parameters, providing a strong foundation for complex language tasks.
- Architecture: Based on the Qwen2.5 family, known for its general-purpose language capabilities.
- Instruction-Tuned: Optimized to follow human instructions effectively, making it suitable for interactive applications.
- Pruned Version: Implies a focus on efficiency, potentially offering a balance between performance and resource usage.
Potential Use Cases
- General Conversational AI: Engaging in natural language dialogues and answering a wide range of queries.
- Instruction Following: Executing commands and generating responses based on explicit instructions.
- Text Generation: Creating coherent and contextually relevant text for various applications.
- Language Understanding: Interpreting and processing natural language inputs.