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README.md

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+---
+license: apache-2.0
+tags:
+  - text-generation
+  - instruction-tuned
+  - llama
+  - gguf
+  - chatbot
+library_name: llama.cpp
+language: en
+datasets:
+  - custom
+model-index:
+  - name: Corelyn NeoMini
+    results: []
+---
+
+
+# Corelyn NeoMini GGUF Model
+
+## Specifications :
+- Model Name: Corelyn NeoMini
+- Base Name: NeoMini-3.2
+- Type: Instruct / Fine-tuned
+- Architecture: LLaMA
+- Size: 3B parameters
+- Organization: Corelyn
+
+## Model Overview
+
+Corelyn NeoMini is a 3-billion parameter LLaMA-based instruction-tuned model, designed for general-purpose assistant tasks and knowledge extraction. It is a fine-tuned variant optimized for instruction-following use cases.
+
+- Fine-tuning type: Instruct
+
+- Base architecture: LLaMA
+
+- Parameter count: 3B
+
+
+### This model is suitable for applications such as:
+
+- Chatbots and conversational AI
+
+- Knowledge retrieval and Q&A
+
+- Code and text generation
+
+- Instruction-following tasks
+
+## Usage
+
+Download from : [NeoMini3.2](https://huggingface.co/CorelynAI/NeoMini/resolve/main/NeoMini_3B.gguf)
+
+```python
+
+# pip install pip install llama-cpp-python
+
+from llama_cpp import Llama
+
+# Load the model (update the path to where your .gguf file is)
+llm = Llama(model_path="path/to/the/file/NeoMini_3B.gguf")
+
+# Create chat completion
+response = llm.create_chat_completion(
+    messages=[{"role": "user", "content": "Create a Haiku about AI"}]
+)
+
+# Print the generated text
+print(response.choices[0].message["content"])
+
+
+```