kelsbeans/qwen3-1.7b-digestive-coach-n119
TEXT GENERATIONPricing:Input $0.32 / Cached $0.064 / Output $1.6Concurrent Unit Cost:1Model Size:2BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 21, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The kelsbeans/qwen3-1.7b-digestive-coach-n119 is a 1.7 billion parameter Qwen3 model developed by kelsbeans. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for specific applications related to digestive health coaching, leveraging its efficient training methodology. This model offers a specialized solution within the Qwen3 family for targeted conversational AI tasks.
Loading preview...
Model Overview
The kelsbeans/qwen3-1.7b-digestive-coach-n119 is a specialized Qwen3 model with approximately 1.7 billion parameters, developed by kelsbeans. It has been fine-tuned from the unsloth/qwen3-1.7b-unsloth-bnb-4bit base model.
Key Characteristics
- Efficient Training: This model was trained significantly faster, achieving a 2x speedup, by utilizing the Unsloth library in conjunction with Huggingface's TRL library. This indicates an optimization for training efficiency.
- Specialized Fine-tuning: The model's name suggests a specific fine-tuning objective related to "digestive coach," implying its intended use in applications requiring knowledge or conversational abilities in this domain.
- Base Architecture: Built upon the Qwen3 architecture, it inherits the foundational capabilities of that model family.
Potential Use Cases
- Health Coaching: Ideal for applications requiring an AI assistant focused on digestive health advice or information.
- Specialized Chatbots: Suitable for creating chatbots tailored to specific health and wellness niches.
- Efficient Deployment: Given its 1.7 billion parameters and optimized training, it may offer a good balance of performance and resource efficiency for targeted applications.