Nina2811aw/qwen-32B-conciousness
TEXT GENERATIONConcurrency Cost:2Model Size:32.8BQuant:FP8Ctx Length:32kPublished:Mar 23, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The Nina2811aw/qwen-32B-conciousness model is a 32.8 billion parameter Qwen2.5-based language model developed by Nina2811aw. Fine-tuned from unsloth/qwen2.5-32b-instruct-bnb-4bit, it was trained using Unsloth and Huggingface's TRL library for accelerated performance. This model is designed for general language generation tasks, leveraging its large parameter count and efficient fine-tuning process.
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Model Overview
Nina2811aw/qwen-32B-conciousness is a 32.8 billion parameter language model, fine-tuned by Nina2811aw. It is based on the Qwen2.5 architecture, specifically building upon the unsloth/qwen2.5-32b-instruct-bnb-4bit model.
Key Characteristics
- Architecture: Qwen2.5-based, a powerful transformer architecture.
- Parameter Count: 32.8 billion parameters, enabling robust language understanding and generation capabilities.
- Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which allowed for a 2x faster training process.
- Context Length: Supports a context length of 32768 tokens, suitable for processing longer inputs and generating extended responses.
Potential Use Cases
- Advanced Text Generation: Capable of generating coherent and contextually relevant text for various applications.
- Instruction Following: Benefits from its instruction-tuned base model, making it suitable for tasks requiring specific directives.
- Research and Development: Provides a large-scale, efficiently fine-tuned model for further experimentation and application development.