sohamb37lexsi/curatorkit-both-filtered-qwen3-1b7

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:May 23, 2026License:apache-2.0Architecture:Transformer Open Weights Warm

The sohamb37lexsi/curatorkit-both-filtered-qwen3-1b7 is a 4 billion parameter Qwen3-based causal language model developed by sohamb37lexsi. This model was fine-tuned using Unsloth, enabling 2x faster training. It is designed for general language tasks, leveraging its Qwen3 architecture for efficient processing.

Loading preview...

Model Overview

The sohamb37lexsi/curatorkit-both-filtered-qwen3-1b7 is a 4 billion parameter language model based on the Qwen3 architecture. Developed by sohamb37lexsi, this model was fine-tuned using the Unsloth library, which significantly accelerated its training process by a factor of two.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/Qwen3-4B.
  • Parameter Count: Features 4 billion parameters, offering a balance between performance and computational efficiency.
  • Training Optimization: Leverages Unsloth for enhanced training speed, making it a more efficient option for deployment or further fine-tuning.
  • License: Distributed under the Apache-2.0 license, allowing for broad use and modification.

Potential Use Cases

This model is suitable for a variety of general natural language processing tasks where the Qwen3 architecture's capabilities are beneficial. Its optimized training suggests it could be a good candidate for applications requiring efficient model iteration or deployment on resource-constrained environments.