taharmasmaliyev07/Qwen2.5-3B-Instruct-E3-BF16
TEXT GENERATIONConcurrency Cost:1Model Size:3.1BQuant:BF16Ctx Length:32kPublished:Apr 17, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The taharmasmaliyev07/Qwen2.5-3B-Instruct-E3-BF16 is a 3.1 billion parameter instruction-tuned causal language model, fine-tuned by taharmasmaliyev07 from unsloth/Qwen2.5-3B-Instruct. This model was trained using Unsloth, enabling faster training times. It is designed for general instruction-following tasks, leveraging its 32K context length for diverse applications.
Loading preview...
Model Overview
The taharmasmaliyev07/Qwen2.5-3B-Instruct-E3-BF16 is a 3.1 billion parameter instruction-tuned language model. It was developed by taharmasmaliyev07 and fine-tuned from the unsloth/Qwen2.5-3B-Instruct base model. A key characteristic of this model's development is its training process, which utilized Unsloth to achieve significantly faster training speeds.
Key Capabilities
- Instruction Following: Designed to accurately follow a wide range of instructions, making it suitable for various NLP tasks.
- Efficient Training: Benefits from the Unsloth framework, indicating potential for more rapid iteration and deployment.
- Context Length: Features a substantial context window of 32,768 tokens, allowing it to process and generate longer, more coherent responses.
Good For
- General-purpose AI applications: Its instruction-tuned nature makes it versatile for tasks like summarization, question answering, and content generation.
- Developers seeking efficient models: The use of Unsloth in its training suggests an emphasis on performance and resource optimization.
- Applications requiring extended context: The 32K context length is beneficial for tasks that involve processing or generating lengthy texts.