AM014/qwen-cpp-optimized-16bit
TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 2, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
AM014/qwen-cpp-optimized-16bit is a 7.6 billion parameter Qwen2 model developed by AM014, fine-tuned from unsloth/qwen2.5-coder-7b-instruct-bnb-4bit. This model was optimized for faster training using Unsloth and Huggingface's TRL library. It is designed for efficient performance, making it suitable for applications requiring a balance of capability and speed.
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Model Overview
AM014/qwen-cpp-optimized-16bit is a 7.6 billion parameter language model, fine-tuned by AM014. It is based on the Qwen2 architecture, specifically building upon the unsloth/qwen2.5-coder-7b-instruct-bnb-4bit model.
Key Characteristics
- Optimized Training: This model was trained significantly faster (2x) using the Unsloth library in conjunction with Huggingface's TRL library. This optimization focuses on accelerating the fine-tuning process.
- Base Model: It leverages the capabilities of the Qwen2.5-coder-7b-instruct model, suggesting a foundation for instruction-following and potentially coding-related tasks.
- Parameter Count: With 7.6 billion parameters, it offers a balance between model size and performance, suitable for various applications.
Potential Use Cases
- Efficient Deployment: Due to its optimized training, this model may be well-suited for scenarios where rapid iteration and deployment of fine-tuned models are crucial.
- Instruction Following: Inheriting from an instruction-tuned base model, it is likely capable of understanding and executing a wide range of user instructions.
- Resource-Conscious Applications: Its 7.6B parameter size makes it a viable option for applications that require a capable language model without the computational overhead of much larger models.