Update README.md

README.md

@@ -3,4 +3,39 @@ license: mit
 language:
 - en
 base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
----
+---
+
+# LLaMA 3 8B - ChatDoctor Model
+
+## Model Description
+This is a fine-tuned version of the **LLaMA 3 8B** model. The model is fine-tuned on medical conversations to assist healthcare professionals and users in understanding medical-related queries. It’s designed for natural language understanding and generation, focusing on medical advice and diagnostics.
+
+- **Base Model:** LLaMA 3 8B
+- **Fine-Tuned On:** Medical QA dataset (or specify other datasets)
+- **Model Type:** Causal Language Model (CLM)
+
+## Intended Use
+This model is intended for generating conversational responses related to medical diagnostics, symptom analysis, or any medical-related inquiry. It is designed to assist in providing informative and preliminary medical guidance based on the fine-tuned datasets.
+
+### Use Cases:
+- Medical chatbots.
+- Healthcare consultation apps.
+- Symptom analysis.
+  
+### Limitations:
+- **Not a replacement for professional medical advice**: The model is trained on limited datasets and should not be used as a standalone diagnostic tool.
+- **Language Bias**: It may show biases based on the data it was trained on.
+
+## How to Use
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the fine-tuned model and tokenizer
+model = AutoModelForCausalLM.from_pretrained("abhiyanta/llama-chatdoctor")
+tokenizer = AutoTokenizer.from_pretrained("abhiyanta/llama-chatdoctor")
+
+# Generate text
+inputs = tokenizer("What are the symptoms of diabetes?", return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=50)
+print(tokenizer.decode(outputs[0]))