Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+language:
+- fa
+library_name: transformers
+tags:
+- text-generation-inference
+inference: false
+pipeline_tag: text-generation
+---
+
+# PersianLLaMA: Towards Building First Persian Large Language Model
+
+## 🌟 Introduction
+Welcome to the home of PersianLLaMA, the pioneering large language model for the Persian language. With 13 billion parameters, this model is trained on a diverse corpus and designed to excel in multiple NLP tasks, setting a new benchmark for Persian language understanding and generation.
+
+![PersianLLaMA](https://huggingface.co/ViraIntelligentDataMining/PersianLLaMA-2-13B/resolve/main/persianllama.png)
+
+## 🛠 Model Description
+PersianLLaMA is not just a model but a comprehensive tool for:
+- 📝 **Text Generation**: Crafting coherent and contextually appropriate text.
+- 🎯 **Instruct Tuning**: Executing tasks based on detailed instructions, ideal for scenarios where the model needs to adhere to specific guidelines or produce outputs tailored to particular requirements.
+- ❓ **Question Answering**: Providing accurate answers to Persian queries.
+- 📊 **Text Summarization**: Condensing Persian texts into precise summaries.
+
+This model has been collaboratively developed by a team of experts, including Mohammad Amin Abbasi, Arash Ghafouri, Mahdi Firouzmandi, Hassan Naderi, and Behrouz Minaei Bidgoli.
+
+## 🚀 Quick Start
+To integrate PersianLLaMA into your project, follow these steps:
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "your-huggingface-username/persianllama"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+prompt = "این متن به فارسی است"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(inputs["input_ids"])
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## 📈 Evaluation and Benchmarks
+PersianLLaMA demonstrates superior performance over existing models, with robust evaluation metrics that highlight its capabilities in natural language understanding and generation.
+
+
+## 📜 Citing PersianLLaMA
+If you find PersianLLaMA useful in your research, please consider citing:
+
+```sql
+@article{abbasi2023persianllama,
+  title={PersianLLaMA: Towards Building First Persian Large Language Model},
+  author={Abbasi, Mohammad Amin and others},
+  journal={https://arxiv.org/abs/2312.15713},
+  year={2023}
+}
+```
+
+
+## 📄 License
+PersianLLaMA is open-sourced under the MIT license.