longtermrisk/Qwen3-4B-Base-ftjob-0511c5edc14e
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Mar 20, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The longtermrisk/Qwen3-4B-Base-ftjob-0511c5edc14e is a 4 billion parameter Qwen3-based causal language model developed by longtermrisk. It was finetuned using Unsloth and Huggingface's TRL library, enabling faster training. This model is designed for general language tasks, leveraging its Qwen3 architecture and a 32768-token context length.
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Model Overview
This model, longtermrisk/Qwen3-4B-Base-ftjob-0511c5edc14e, is a 4 billion parameter language model based on the Qwen3 architecture. It was developed by longtermrisk and is licensed under Apache-2.0.
Key Characteristics
- Base Model: Finetuned from
unsloth/Qwen3-4B-Base. - Training Efficiency: The model was trained significantly faster using Unsloth and Huggingface's TRL library, highlighting an optimized finetuning process.
- Context Length: Features a substantial context window of 32768 tokens, allowing for processing longer inputs and generating more coherent, extended outputs.
Potential Use Cases
- General Language Understanding: Suitable for a wide range of natural language processing tasks due to its base Qwen3 architecture.
- Applications Requiring Efficient Finetuning: Demonstrates the potential for rapid adaptation to specific downstream tasks, benefiting from the Unsloth-accelerated training methodology.
- Research and Development: Can serve as a foundation for further experimentation and finetuning on custom datasets, particularly where training speed is a critical factor.