Update README.md

README.md

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 ## Llama-3.1-8B-Instruct-Mental-Health-Classification
 This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on an [suchintikasarkar/sentiment-analysis-for-mental-health](https://www.kaggle.com/datasets/suchintikasarkar/sentiment-analysis-for-mental-health) dataset.
 
+## Tutorial
+
+Get started with the new Llama models and customize Llama-3.1-8B-It to predict various mental health disorders from the text by following the [Fine-Tuning Llama 3.1 for Text Classification](https://www.datacamp.com/tutorial/fine-tuning-llama-3-1) tutorial. 
+
+## Use with Transformers
+
+```python
+from transformers import AutoTokenizer,AutoModelForCausalLM,pipeline
+import torch
+
+model_id = "kingabzpro/Llama-3.1-8B-Instruct-Mental-Health-Classification"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+
+model = AutoModelForCausalLM.from_pretrained(
+        model_id,
+        return_dict=True,
+        low_cpu_mem_usage=True,
+        torch_dtype=torch.float16,
+        device_map="auto",
+        trust_remote_code=True,
+)
+
+text = "I'm trapped in a storm of emotions that I can't control, and it feels like no one understands the chaos inside me"
+prompt = f"""Classify the text into Normal, Depression, Anxiety, Bipolar, and return the answer as the corresponding mental health disorder label.
+text: {text}
+label: """.strip()
+
+pipe = pipeline(
+    "text-generation",
+    model=model,
+    tokenizer=tokenizer,
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+
+outputs = pipe(prompt, max_new_tokens=2, do_sample=True, temperature=0.1)
+
+print(outputs[0]["generated_text"].split("label: ")[-1].strip())
+
+# Depression
+```
 ## Results
 
 ```bash