Smilesjs/chemsmart-qwen2.5-coder-3b-instruct-v13
The Smilesjs/chemsmart-qwen2.5-coder-3b-instruct-v13 is a 3.1 billion parameter instruction-tuned causal language model developed by Smilesjs. Finetuned from unsloth/Qwen2.5-Coder-3B-Instruct-bnb-4bit, this model was trained using Unsloth and Huggingface's TRL library for accelerated performance. It is designed for general instruction-following tasks, leveraging its Qwen2.5 architecture and 32768 token context length.
Loading preview...
Model Overview
The Smilesjs/chemsmart-qwen2.5-coder-3b-instruct-v13 is a 3.1 billion parameter instruction-tuned language model developed by Smilesjs. It is built upon the Qwen2.5 architecture, specifically finetuned from the unsloth/Qwen2.5-Coder-3B-Instruct-bnb-4bit base model.
Key Characteristics
- Architecture: Qwen2.5-based, a robust causal language model family.
- Parameter Count: 3.1 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a substantial context window of 32768 tokens, enabling processing of longer inputs and maintaining conversational coherence.
- Training Optimization: This model was finetuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- License: Distributed under the Apache-2.0 license, allowing for broad usage and modification.
Use Cases
This model is suitable for a variety of instruction-following tasks, benefiting from its optimized training and Qwen2.5 foundation. Its substantial context length makes it particularly useful for applications requiring understanding and generation based on extensive input.