Quantizations of https://huggingface.co/prithivMLmods/QwQ-LCoT-7B-Instruct
Inference Clients/UIs
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:
- Dataset Name: amphora/QwQ-LongCoT-130K
- Size: 133k examples.
- Focus: Chain-of-Thought reasoning for complex tasks.
Use Cases:
Instruction Following:
Handle user instructions effectively, even for multi-step tasks.Reasoning Tasks:
Perform logical reasoning and generate detailed step-by-step solutions.Text Generation:
Generate coherent, context-aware responses.
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