Update README.md

README.md

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 This model was converted to GGUF format from [`prithivMLmods/QwQ-LCoT-7B-Instruct`](https://huggingface.co/prithivMLmods/QwQ-LCoT-7B-Instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/prithivMLmods/QwQ-LCoT-7B-Instruct) for more details on the model.
 
+---
+Model details:
+-
+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.
+
+		Key Features:
+	
+Model Size:  
+
+7.62B parameters (FP16 precision).
+
+Model Sharding:  
+
+The model weights are split into 4 shards (safetensors) for efficient storage and download:
+model-00001-of-00004.safetensors (4.88 GB)
+model-00002-of-00004.safetensors (4.93 GB)
+model-00003-of-00004.safetensors (4.33 GB)
+model-00004-of-00004.safetensors (1.09 GB)
+
+Tokenizer:  
+
+Byte-pair encoding (BPE) based.
+Files included:
+vocab.json (2.78 MB)
+merges.txt (1.82 MB)
+tokenizer.json (11.4 MB)
+
+Special tokens mapped in special_tokens_map.json (e.g., <pad>, <eos>).
+
+Configuration Files:  
+
+config.json: Defines model architecture and hyperparameters.
+generation_config.json: Settings for inference and text generation tasks.
+
+		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.
+
+---
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)