boyatilak123/StudyLap-Tutor-v2

TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 23, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

boyatilak123/StudyLap-Tutor-v2 is a 7.6 billion parameter Qwen2.5-Instruct model, fine-tuned by boyatilak123 using Unsloth and Huggingface's TRL library. This model is optimized for efficient training, achieving 2x faster fine-tuning. It is designed for general instruction-following tasks, leveraging the Qwen2.5 architecture for robust performance.

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Model Overview

boyatilak123/StudyLap-Tutor-v2 is a 7.6 billion parameter instruction-tuned language model based on the Qwen2.5 architecture. Developed by boyatilak123, this model was fine-tuned using the Unsloth library in conjunction with Huggingface's TRL library, enabling significantly faster training.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/Qwen2.5-7B-Instruct-bnb-4bit.
  • Efficient Training: Leverages Unsloth for a reported 2x faster fine-tuning process, making it efficient for custom adaptations.
  • Parameter Count: Features 7.6 billion parameters, providing a balance between performance and computational requirements.
  • Context Length: Supports a substantial context window of 32768 tokens, suitable for processing longer inputs and maintaining conversational coherence.

Use Cases

This model is well-suited for applications requiring a capable instruction-following model with the efficiency benefits of Unsloth's training optimizations. Its Qwen2.5 foundation makes it versatile for various natural language processing tasks.