valixonov04/qwen-7b-kiberbase
TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 3, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
valixonov04/qwen-7b-kiberbase is a 7.6 billion parameter Qwen2 model developed by valixonov04. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is based on the unsloth/qwen2.5-7b-unsloth-bnb-4bit model and is suitable for tasks benefiting from its Qwen2 architecture and efficient fine-tuning process.
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Model Overview
valixonov04/qwen-7b-kiberbase is a 7.6 billion parameter language model based on the Qwen2 architecture. It was developed by valixonov04 and fine-tuned from the unsloth/qwen2.5-7b-unsloth-bnb-4bit model. A key characteristic of this model is its training methodology, which leveraged Unsloth and Huggingface's TRL library, resulting in a 2x faster fine-tuning process.
Key Capabilities
- Qwen2 Architecture: Inherits the foundational capabilities of the Qwen2 model family.
- Efficient Fine-tuning: Benefits from the Unsloth framework, which optimizes the fine-tuning process for speed.
- Parameter Count: With 7.6 billion parameters, it offers a balance between performance and computational requirements.
Good For
- Applications requiring a Qwen2 base model: Suitable for tasks where the Qwen2 architecture is a preferred choice.
- Developers interested in Unsloth-trained models: Provides an example of a model fine-tuned with Unsloth for efficiency.
- General language generation tasks: Can be adapted for various natural language processing applications.