README.md

---
license: mit
language:
- en
base_model:
- meta-llama/Meta-Llama-3-8B-Instruct
library_name: transformers
---

# 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")