Pranjalps1/Qwen3.5-2B-Code-Base
Pranjalps1/Qwen3.5-2B-Code-Base is a 2.3 billion parameter Qwen3.5 model developed by Pranjalps1. This model was finetuned from Pranjalps1/Qwen3.5-2B-think and optimized for faster training using Unsloth and Huggingface's TRL library. With a 32768 token context length, it is designed for general text generation tasks, leveraging its efficient training methodology.
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Model Overview
Pranjalps1/Qwen3.5-2B-Code-Base is a 2.3 billion parameter Qwen3.5 model, developed by Pranjalps1. It is a finetuned variant of the Pranjalps1/Qwen3.5-2B-think base model, designed for efficient performance in text generation tasks.
Key Characteristics
- Efficient Training: This model was finetuned using Unsloth and Huggingface's TRL library, enabling training up to 2x faster compared to standard methods.
- Base Architecture: Built upon the Qwen3.5 architecture, known for its robust language understanding capabilities.
- Parameter Count: Features 2.3 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a substantial context window of 32768 tokens, allowing for processing longer inputs and generating coherent, extended outputs.
Use Cases
This model is suitable for a variety of text generation applications where efficient inference and a good balance of model size and performance are desired. Its finetuning process suggests potential benefits for tasks requiring rapid iteration or deployment on resource-constrained environments.