Update README.md

README.md

@@ -1,72 +1,75 @@
----
-license: apache-2.0
-tags:
-  - text-generation
-  - instruction-tuned
-  - maincoder
-  - gguf
-  - chatbot
-library_name: llama.cpp
-language: en
-datasets:
-  - custom
-model-index:
-  - name: Corelyn Neosepcyn Leon
-    results: []
----
-
-
-# Corelyn NeoMini GGUF Model
-
-## Specifications :
-- Model Name: Corelyn Neosepcyn Leon
-- Base Name: Leon_1B
-- Type: Instruct / Fine-tuned
-- Architecture: Maincoder
-- Size: 1B parameters
-- Organization: Corelyn
-
-## Model Overview
-
-Corelyn Neosepcyn Leon is a 1-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: Maincoder
-
-- Parameter count: 3B
-
-
-### This model is suitable for applications such as:
-
-- Algorithms
-
-- Websites
-
-- Python, JavaScript, Java...
-
-- Code and text generation
-
-## Usage
-
-Download from : [LeonCode_1B](https://huggingface.co/CorelynAI/LeonCode/blob/main/LeonCode_1B.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/LeonCode_1B.gguf")
-
-# Create chat completion
-response = llm.create_chat_completion(
-    messages=[{"role": "user", "content": "Create a python sorting algorithm"}]
-)
-
-# Print the generated text
-print(response.choices[0].message["content"])
-
-
+---
+license: apache-2.0
+tags:
+- text-generation
+- instruction-tuned
+- maincoder
+- gguf
+- chatbot
+library_name: llama.cpp
+language: en
+datasets:
+- custom
+model-index:
+- name: Corelyn Neosepcyn Leon
+  results: []
+base_model:
+- yourGGUF/Maincoder-1B_GGUF
+---
+
+![logo](./images/neospecyn.png)
+
+# Corelyn Leon GGUF Model
+
+## Specifications :
+- Model Name: Corelyn Neosepcyn Leon
+- Base Name: Leon_1B
+- Type: Instruct / Fine-tuned
+- Architecture: Maincoder
+- Size: 1B parameters
+- Organization: Corelyn
+
+## Model Overview
+
+Corelyn Neosepcyn Leon is a 1-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: Maincoder
+
+- Parameter count: 3B
+
+
+### This model is suitable for applications such as:
+
+- Algorithms
+
+- Websites
+
+- Python, JavaScript, Java...
+
+- Code and text generation
+
+## Usage
+
+Download from : [LeonCode_1B](https://huggingface.co/CorelynAI/LeonCode/blob/main/LeonCode_1B.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/LeonCode_1B.gguf")
+
+# Create chat completion
+response = llm.create_chat_completion(
+    messages=[{"role": "user", "content": "Create a python sorting algorithm"}]
+)
+
+# Print the generated text
+print(response.choices[0].message["content"])
+
+
 ```