Quantizations of https://huggingface.co/prithivMLmods/QwQ-LCoT-7B-Instruct

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From original readme

The QwQ-LCoT-7B-Instruct is a fine-tuned language model designed for advanced reasoning and instruction-following tasks. It leverages the Qwen2.5-7B base model and has been fine-tuned on the amphora/QwQ-LongCoT-130K dataset, focusing on chain-of-thought (CoT) reasoning.

Training Dataset:


Use Cases:

  1. Instruction Following:
    Handle user instructions effectively, even for multi-step tasks.

  2. Reasoning Tasks:
    Perform logical reasoning and generate detailed step-by-step solutions.

  3. Text Generation:
    Generate coherent, context-aware responses.


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Inference Examples
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