Update README.md

README.md

@@ -29,4 +29,33 @@ It is built on Nemo 12b and trained on different datasets as well as some layer
 
 - **Base model:** mistralai/Mistral-Nemo-Base-2407
 - **Parameter count:** ~12 billion
-- **Architecture specifics:** Transformer-based language model
+- **Architecture specifics:** Transformer-based language model
+
+## Intended Use 🎯
+As an advanced language model for various natural language processing tasks, including but not limited to text generation (excels in chat), question-answering, and analysis.
+
+## Ethical Considerations 🤔
+As a model based on multiple sources, Zinakha-12b may inherit biases and limitations from its constituent models. Users should be aware of potential biases in generated content and use the model responsibly.
+
+## Performance and Evaluation
+Performance metrics and evaluation results for Zinakha-12b are yet to be determined. Users are encouraged to contribute their findings and benchmarks.
+
+## Limitations and Biases
+The model may exhibit biases present in its training data and constituent models. It's crucial to critically evaluate the model's outputs and use them in conjunction with human judgment.
+
+## Additional Information
+For more details on the base model and constituent models, please refer to their respective model cards and documentation.
+
+## How to Use
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model = AutoModelForCausalLM.from_pretrained("aixonlab/Zinakha-12b")
+tokenizer = AutoTokenizer.from_pretrained("aixonlab/Zinakha-12b")
+
+prompt = "Once upon a time"
+input_ids = tokenizer(prompt, return_tensors="pt").input_ids
+
+generated_ids = model.generate(input_ids, max_length=100)
+generated_text = tokenizer.decode(generated_ids, skip_special_tokens=True)
+print(generated_text)