Update README.md

README.md

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 pipeline_tag: text-generation
+license: cc-by-nc-4.0
 ---
 
 # GodziLLa-30B 🦖
 Released July 9, 2023
 
 ## Model Description
-GodziLLa-30B is an experimental combination of various LoRAs with CalderaAI's [Lazarus-30B](https://huggingface.co/CalderaAI/30B-Lazarus). This composite model is not meant for actual use, in any capacity, outside of research on intercompeting LoRA adapter behavior. Additionally, since this is inherently a LlaMA model, **commercial use is prohibited**. This model's primary purpose is to stress test the limitations of composite LLMs and observe its performance with respect to other LLMs available on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
+GodziLLa-30B is an experimental combination of various proprietary Maya LoRAs with CalderaAI's [Lazarus-30B](https://huggingface.co/CalderaAI/30B-Lazarus). This composite model is not meant for any other use outside of research on competing LoRA adapter behavior. More specifically, since this is inherently a LlaMA model, **commercial use is prohibited**. This model's primary purpose is to stress test the limitations of composite LLMs and observe its performance with respect to other LLMs available on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
 
 ## Recommended Prompt Format
 Alpaca's instruction is the recommended prompt format, but Vicuna's instruction format may also work.
 
+## Usage
+To use GodziLLa-30B, you are required to provide attribution in accordance with the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license. Please include the following attribution notice when utilizing GodziLLa-30B in your work:
+
+```python
+# This code uses GodziLLa-30B, a language model developed by Maya Philippines.
+# The model is licensed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.
+# For more information, visit: https://creativecommons.org/licenses/by-nc/4.0/
+
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("MayaPH/GodziLLa-30B")
+
+model = AutoModelForCausalLM.from_pretrained("MayaPH/GodziLLa-30B")
+```
+
+Please ensure that you include the relevant attribution notice in your code or any other form of usage and restrict your usage to non-commercial use to comply with the license terms.
+
 ## Ethical Considerations
 When using GodziLLa-30B, it is important to consider the following ethical considerations: