Update README.md

README.md

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 This model was converted to GGUF format from [`Qwen/Qwen3-4B`](https://huggingface.co/Qwen/Qwen3-4B) 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/Qwen/Qwen3-4B) for more details on the model.
 
+---
+Qwen3 is the latest generation of large language models in Qwen 
+series, offering a comprehensive suite of dense and mixture-of-experts 
+(MoE) models. Built upon extensive training, Qwen3 delivers 
+groundbreaking advancements in reasoning, instruction-following, agent 
+capabilities, and multilingual support, with the following key features:
+
+Uniquely support of seamless switching between thinking mode (for complex logical reasoning, math, and coding) and non-thinking mode (for efficient, general-purpose dialogue) within single model, ensuring optimal performance across various scenarios.
+Significantly enhancement in its reasoning capabilities,
+ surpassing previous QwQ (in thinking mode) and Qwen2.5 instruct models 
+(in non-thinking mode) on mathematics, code generation, and commonsense 
+logical reasoning.
+Superior human preference alignment, excelling in 
+creative writing, role-playing, multi-turn dialogues, and instruction 
+following, to deliver a more natural, engaging, and immersive 
+conversational experience.
+Expertise in agent capabilities, enabling precise 
+integration with external tools in both thinking and unthinking modes 
+and achieving leading performance among open-source models in complex 
+agent-based tasks.
+Support of 100+ languages and dialects with strong capabilities for multilingual instruction following and translation.
+
+Model Overview
+-
+Qwen3-4B has the following features:
+
+Type: Causal Language Models
+
+Training Stage: Pretraining & Post-training
+
+Number of Parameters: 4.0B
+
+Number of Paramaters (Non-Embedding): 3.6B
+
+Number of Layers: 36
+
+Number of Attention Heads (GQA): 32 for Q and 8 for KV
+
+Context Length: 32,768 natively and 131,072 tokens with YaRN.
+
+---
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)