allenwoods823/AlenAI-4B
VISIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:4.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Sep 23, 2026License:mitArchitecture:Transformer Open Weights Featherless Exclusive Cold
AlenAI-4B by allenwoods823 is a 4.5 billion parameter language model, finetuned from Qwen/Qwen3.5-4B. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for general language tasks, leveraging its efficient training methodology.
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AlenAI-4B Overview
AlenAI-4B is a 4.5 billion parameter language model developed by allenwoods823. It is a finetuned version of the Qwen/Qwen3.5-4B base model, indicating its foundation in the Qwen architecture.
Key Characteristics
- Efficient Training: This model was trained with a focus on efficiency, utilizing Unsloth and Huggingface's TRL library. This combination enabled a 2x faster training process compared to standard methods.
- Base Model: Built upon the robust Qwen3.5-4B model, AlenAI-4B inherits its foundational language understanding and generation capabilities.
Potential Use Cases
- General Language Tasks: Suitable for a wide range of applications requiring text generation, comprehension, and instruction following.
- Resource-Efficient Deployment: Its optimized training suggests potential for more efficient fine-tuning or deployment in environments where training speed is a factor.