Update README.md

README.md

@@ -11,12 +11,43 @@ language:
 - en
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-# Uploaded  model
+![Zara-14b Banner](https://cdn-uploads.huggingface.co/production/uploads/66dcee3321f901b049f48002/uBEgIFXSUhUFwRaVuXYvV.png)
 
-- **Developed by:** aixonlab
-- **License:** apache-2.0
-- **Finetuned from model :** aixonlab/Zara-14b-v1.1
+# Zara 14b v1.2 🧙‍♂️
 
-This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+Zara 14b tries to become the perfect companion for any chat which involves multiple roles. The ability to understand context is pretty awesome and excels in creativity and storytelling.
+It is built on Lamarck 14B v0.7 and trained on different datasets as well as some layer merges to ehance its capabilities.
+
+## Model Details 📊
+
+- **Developed by:** Aixon Lab
+- **Model type:** Causal Language Model
+- **Language(s):** English (primarily), may support other languages
+- **License:** Apache 2.0
+- **Repository:** https://huggingface.co/aixonlab/Zara-14b-v1.2
+
+## Quantization
+- **GGUF:** https://huggingface.co/mradermacher/Zara-14b-v1.2-GGUF
+
+## Model Architecture 🏗️
+
+- **Base model:** aixonlab/Zara-14b-v1.1
+- **Parameter count:** ~14 billion
+- **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, Zara 14b 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 Zara 14b 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.
+