Update README.md

README.md

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-# Jaleah AI Coder Model
+---
+language: 
+- en
+- code
+tags:
+- code-generation
+- ai-assistant
+- programming
+license: mit
+datasets:
+- custom
+metrics:
+- code-completion-accuracy
+model-index:
+- name: Jaleah AI Coder
+  results:
+  - task: 
+      type: text-generation
+      name: Code Generation
+    dataset:
+      name: Custom Programming Dataset
+      type: custom
+    metrics:
+      - type: code-completion
+        value: experimental
+---
 
-Custom AI code generation model for intelligent programming assistance.
+# Model Card: Jaleah AI Coder
 
-## Usage
+## Model Details
+- **Developed by**: teckmill
+- **Model type**: Code Generation AI
+- **Primary Language**: Python
+- **Version**: 1.0
 
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
+## Model Purpose
+Jaleah AI is an intelligent code generation model designed to assist developers by:
+- Generating code snippets
+- Providing programming suggestions
+- Helping with code completion
 
-model = AutoModelForCausalLM.from_pretrained('teckmill/Jaleah-AI')
-tokenizer = AutoTokenizer.from_pretrained('teckmill/Jaleah-AI')
-```
+## Model Capabilities
+- Understands programming context
+- Generates syntactically correct code
+- Supports multiple programming paradigms
 
 ## Limitations
-- Experimental model
-- Requires careful review
-- May generate incorrect code
+- Experimental technology
+- May generate incorrect or incomplete code
+- Requires human verification and review
+
+## Ethical Considerations
+- Not intended to replace human developers
+- Should be used as an assistive tool
+- Always review generated code before implementation
+
+## Usage Recommendations
+1. Use as a coding assistant
+2. Always validate generated code
+3. Do not rely solely on AI-generated code for critical systems
+
+## Licensing
+MIT License
+
+## Contact
+For more information, issues, or collaboration:
+- GitHub: [Your GitHub Repository]
+- Email: [Your Contact Email]
+
+