CompassioninMachineLearning/qwen-urban-web-s3407-part1
TEXT GENERATIONPricing:Input $0.468 / Output $1.82Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Oct 16, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The CompassioninMachineLearning/qwen-urban-web-s3407-part1 is an 8 billion parameter Qwen3 model developed by CompassioninMachineLearning, fine-tuned from CompassioninMachineLearning/qwen-urban-web-seed3407-CPT-best. It was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. This model is designed for general language tasks, leveraging its Qwen3 architecture and 32768 token context length for robust performance.
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Overview
CompassioninMachineLearning/qwen-urban-web-s3407-part1 is an 8 billion parameter Qwen3 model developed by CompassioninMachineLearning. It is a fine-tuned version of the CompassioninMachineLearning/qwen-urban-web-seed3407-CPT-best model, utilizing the Qwen3 architecture.
Key Capabilities
- Efficient Training: This model was trained 2x faster by leveraging the Unsloth library in conjunction with Huggingface's TRL library, indicating an optimized training process.
- Qwen3 Architecture: Built upon the Qwen3 foundation, it benefits from the advancements and capabilities inherent to this model family.
- General Language Tasks: With 8 billion parameters and a 32768 token context length, it is suitable for a broad range of natural language processing applications.
Good for
- Applications requiring efficient fine-tuning: Developers looking for models that can be fine-tuned rapidly will benefit from its Unsloth-optimized training.
- General-purpose language understanding and generation: Its Qwen3 base and substantial parameter count make it versatile for various text-based tasks.
- Projects needing a robust Qwen3-based model: Ideal for use cases where the Qwen3 architecture's strengths are a good fit.