Update README.md

README.md

@@ -43,4 +43,40 @@ My model is now on the Arabic leaderboard.
 
 Please refer to https://github.com/Slim205/Arabicllm/ for more details.
 
+# Using the Model
+
+The model uses `transformers` to generate responses based on the provided inputs. Here’s an example code to use the model:
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from peft import PeftModel
+import torch
+
+model_id = "google/gemma-2-2b-it"
+peft_model_id = "Slim205/Barka-2b-it"
+
+model = AutoModelForCausalLM.from_pretrained(model_id).to("cuda")
+tokenizer = AutoTokenizer.from_pretrained("Slim205/Barka-2b-it")
+model1 = PeftModel.from_pretrained(model, peft_model_id)
+
+input_text = "ما هي عاصمة تونس؟"  # "What is the capital of Tunisia?"
+chat = [
+    { "role": "user", "content": input_text },
+]
+
+prompt = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt")
+outputs = model.generate(
+    input_ids=inputs.to(model.device),
+    max_new_tokens=32,
+    top_p=0.9,
+    do_sample=True
+)
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+```
+
+You can adjust any additional sections or formatting as necessary!
+
 # Feel free to use this model and send me your feedback. Together, we can advance Arabic LLM development!