longtermrisk/Qwen3-4B-Instruct-2507-ftjob-35d4281f0d6c

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

The longtermrisk/Qwen3-4B-Instruct-2507-ftjob-35d4281f0d6c is a 4 billion parameter instruction-tuned Qwen3 model, developed by longtermrisk. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general instruction-following tasks, leveraging its 32768 token context length for processing longer inputs.

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Overview

This model, longtermrisk/Qwen3-4B-Instruct-2507-ftjob-35d4281f0d6c, is a 4 billion parameter instruction-tuned variant of the Qwen3 architecture. Developed by longtermrisk, it was fine-tuned from the unsloth/Qwen3-4B-Instruct-2507 base model.

Key Characteristics

  • Architecture: Qwen3-based, a powerful transformer model family.
  • Parameter Count: 4 billion parameters, offering a balance between performance and efficiency.
  • Context Length: Supports a substantial 32768 tokens, allowing for processing of extensive inputs and maintaining conversational context over longer interactions.
  • Training Methodology: Fine-tuned using the Unsloth library in conjunction with Huggingface's TRL library, which facilitated a 2x faster training process.

Primary Use Case

This model is well-suited for general instruction-following applications where a moderately sized, efficient model with a large context window is beneficial. Its fine-tuned nature suggests proficiency in understanding and executing a wide range of user commands and queries.