abhinav0231/Qwen2.5-1.5B-reasoning-warmup
TEXT GENERATIONConcurrency Cost:1Model Size:1.5BQuant:BF16Ctx Length:32kPublished:Apr 19, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The abhinav0231/Qwen2.5-1.5B-reasoning-warmup is a 1.5 billion parameter Qwen2.5 model, developed by abhinav0231 and fine-tuned from unsloth/qwen2.5-1.5b-instruct-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for general language tasks, leveraging its efficient training methodology.
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Model Overview
The abhinav0231/Qwen2.5-1.5B-reasoning-warmup is a 1.5 billion parameter language model based on the Qwen2.5 architecture. Developed by abhinav0231, this model was fine-tuned from the unsloth/qwen2.5-1.5b-instruct-unsloth-bnb-4bit base model.
Key Characteristics
- Efficient Training: This model was trained significantly faster, achieving a 2x speedup, by utilizing Unsloth and Huggingface's TRL library. This indicates an optimization in the fine-tuning process.
- Base Model: It builds upon the
Qwen2.5-1.5B-Instructfoundation, suggesting capabilities for instruction-following and general language generation tasks. - License: The model is released under the Apache-2.0 license, allowing for broad use and distribution.
Potential Use Cases
Given its instruction-tuned base and efficient training, this model is suitable for:
- General text generation and completion.
- Instruction-following tasks where a smaller, efficiently trained model is preferred.
- Applications requiring a balance of performance and resource efficiency.