gustajunq/Lumen-4B-Instruct

TEXT GENERATIONConcurrent Unit Cost:1Model Size:4BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 7, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

gustajunq/Lumen-4B-Instruct is a 4 billion parameter instruction-tuned causal language model developed by gustajunq. This Qwen3-based model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general instruction-following tasks, leveraging its efficient training methodology.

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Model Overview

gustajunq/Lumen-4B-Instruct is a 4 billion parameter instruction-tuned language model based on the Qwen3 architecture. Developed by gustajunq, this model was fine-tuned from unsloth/qwen3-4b-base-unsloth-bnb-4bit using the Unsloth library in conjunction with Huggingface's TRL library. A key characteristic of this model's development is its optimized training process, which was reportedly 2x faster due to the use of Unsloth.

Key Capabilities

  • Instruction Following: Designed to respond effectively to a wide range of user instructions.
  • Efficient Training: Benefits from a fine-tuning process that emphasizes speed and resource optimization.
  • Qwen3 Architecture: Leverages the foundational capabilities of the Qwen3 model family.

Good For

  • General Purpose Chatbots: Suitable for applications requiring conversational AI.
  • Text Generation: Can be used for various text generation tasks based on prompts.
  • Rapid Prototyping: Its efficient training suggests it could be a good candidate for projects where quick iteration and deployment are important.

Finetunes
1 models