PratikChatterjee1280/qwen25-7b-ncert-v5
TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kTool Calling:SupportedPublished:Jun 10, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
PratikChatterjee1280/qwen25-7b-ncert-v5 is a 7.6 billion parameter Qwen2.5 model developed by PratikChatterjee1280. This instruction-tuned causal language model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language understanding and generation tasks, leveraging its Qwen2.5 architecture for robust performance.
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Overview
PratikChatterjee1280/qwen25-7b-ncert-v5 is a 7.6 billion parameter instruction-tuned Qwen2.5 model. Developed by PratikChatterjee1280, this model was fine-tuned from unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit.
Key Capabilities
- Efficient Training: The model was trained 2x faster utilizing Unsloth and Huggingface's TRL library, indicating an optimized training process.
- Qwen2.5 Architecture: Based on the Qwen2.5 family, it inherits the robust capabilities of this architecture for various natural language processing tasks.
- Instruction Following: As an instruction-tuned model, it is designed to understand and execute user prompts effectively.
Good For
- General text generation and understanding tasks.
- Applications requiring a 7.6B parameter model with efficient training origins.
- Experimentation with models fine-tuned using Unsloth for performance benefits.