abhiyanta/Llama-chatDoctor

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

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")