platypus123/EXACT-Qwen-Trained
TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kPublished:May 18, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Warm
EXACT-Qwen-Trained is a 7.6 billion parameter Qwen2.5-based instruction-tuned causal language model developed by platypus123. This model was finetuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general language tasks, leveraging the Qwen2.5 architecture for robust performance.
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Model Overview
platypus123/EXACT-Qwen-Trained is a 7.6 billion parameter instruction-tuned model based on the Qwen2.5 architecture. It was developed by platypus123 and finetuned from the unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit base model.
Key Characteristics
- Architecture: Qwen2.5-based, a powerful causal language model family.
- Training Efficiency: This model was trained significantly faster using the Unsloth library in conjunction with Huggingface's TRL library, indicating an optimized finetuning process.
- License: Distributed under the Apache-2.0 license, allowing for broad use and modification.
Potential Use Cases
Given its Qwen2.5 foundation and instruction-tuned nature, this model is suitable for a variety of general-purpose natural language processing tasks, including:
- Text generation and completion
- Instruction following
- Question answering
- Summarization