gjyotin305/Qwen2.5-3B-Instruct_new_alpaca_007
TEXT GENERATIONConcurrency Cost:1Model Size:3.1BQuant:BF16Ctx Length:32kPublished:Jan 11, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
gjyotin305/Qwen2.5-3B-Instruct_new_alpaca_007 is a 3.1 billion parameter instruction-tuned causal language model developed by gjyotin305, fine-tuned from unsloth/Qwen2.5-3B-Instruct. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for general instruction-following tasks, leveraging its efficient training methodology.
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Model Overview
gjyotin305/Qwen2.5-3B-Instruct_new_alpaca_007 is a 3.1 billion parameter instruction-tuned language model, developed by gjyotin305. It is based on the Qwen2.5-3B-Instruct architecture and has a context length of 32768 tokens.
Key Characteristics
- Efficient Training: This model was fine-tuned using Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
- Instruction-Tuned: Optimized for following instructions and generating coherent, relevant responses based on prompts.
- Apache-2.0 License: Released under a permissive license, allowing for broad use and distribution.
Potential Use Cases
- General Purpose Chatbots: Suitable for conversational AI applications requiring instruction adherence.
- Text Generation: Can be used for various text generation tasks where a smaller, efficient model is beneficial.
- Research and Development: Provides a base for further experimentation and fine-tuning on specific datasets, particularly for those interested in efficient training methodologies.