Bialy17/qwen-finetuned-2500
TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kPublished:Apr 27, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
Bialy17/qwen-finetuned-2500 is a 7.6 billion parameter Qwen2 model developed by Bialy17, fine-tuned from unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training speeds. It is designed for general instruction-following tasks, leveraging its Qwen2 architecture and efficient fine-tuning process.
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Model Overview
Bialy17/qwen-finetuned-2500 is a 7.6 billion parameter Qwen2 model, developed by Bialy17 and licensed under Apache-2.0. It was fine-tuned from the unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit base model.
Key Characteristics
- Efficient Training: This model was trained significantly faster, achieving 2x speed improvements, by utilizing Unsloth and Huggingface's TRL library. This indicates an optimization in the fine-tuning process rather than a change in the core architecture.
- Base Model: Built upon the Qwen2.5-7B-Instruct architecture, suggesting strong general instruction-following capabilities inherited from its foundation.
Good For
- Instruction Following: As an instruction-tuned model, it is suitable for a wide range of tasks requiring the model to follow specific prompts and instructions.
- Resource-Efficient Deployment: The use of Unsloth for training implies a focus on efficiency, which can translate to more optimized inference or further fine-tuning for users with limited computational resources.