longtermrisk/Qwen3-4B-Instruct-2507-ftjob-e3f6e890af59
The longtermrisk/Qwen3-4B-Instruct-2507-ftjob-e3f6e890af59 is a 4 billion parameter instruction-tuned Qwen3 model developed by longtermrisk, fine-tuned using Unsloth and Huggingface's TRL library. This model was trained significantly faster, leveraging optimized training techniques. It is designed for general instruction-following tasks, building upon the capabilities of the Qwen3 architecture.
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Model Overview
This model, developed by longtermrisk, is an instruction-tuned variant of the Qwen3-4B architecture, specifically fine-tuned from unsloth/Qwen3-4B-Instruct-2507. It leverages the Unsloth library in conjunction with Huggingface's TRL library, which enabled a 2x faster training process compared to standard methods.
Key Characteristics
- Base Model: Qwen3-4B-Instruct
- Parameter Count: 4 billion parameters
- Context Length: 32768 tokens
- Training Optimization: Utilizes Unsloth for accelerated fine-tuning.
- License: Released under the Apache-2.0 license.
Use Cases
This model is suitable for a variety of general instruction-following applications, benefiting from its efficient fine-tuning process. Its 4 billion parameters make it a good candidate for scenarios where a balance between performance and computational efficiency is desired.