Overview

The duttaturja/MLPredic-4B is a 4 billion parameter language model based on the Qwen3 architecture. Developed by duttaturja, this model was fine-tuned from unsloth/qwen3-4b-unsloth-bnb-4bit and leverages the Unsloth library in conjunction with Huggingface's TRL library for training. A key characteristic of its development is the reported 2x faster training speed achieved through the use of Unsloth.

Key Characteristics

• Model Architecture: Qwen3
• Parameter Count: 4 billion parameters
• Context Length: Supports a substantial 40960 tokens, enabling the processing of extensive inputs.
• Training Efficiency: Benefits from Unsloth for significantly accelerated training.
• License: Released under the Apache-2.0 license.

Good For

This model is particularly well-suited for use cases where:

• Efficient deployment of a 4B parameter Qwen3 model is desired.
• Applications requiring a large context window (40960 tokens) are critical.
• Developers are looking for a model fine-tuned with accelerated training techniques like Unsloth.