Model README Model Overview Model Name: [Your Model Name] Base Model: unsloth/meta-llama-3.1-8b-bnb-4bit Developed by: varma007ut License: Apache 2.0 Description This model is a fine-tuned version of the unsloth/meta-llama-3.1-8b-bnb-4bit designed specifically for text generation tasks in the medical domain. It leverages a substantial dataset of medical texts to improve its performance and relevance in generating medical-related content.

Fine-tuning Details Fine-tuned Data: The model has been fine-tuned on medicinal data, enhancing its ability to understand and generate contextually appropriate medical text. Objective: The fine-tuning process aims to make the model proficient in medical terminology, guidelines, and general knowledge pertinent to healthcare professionals. Installation To use this model, ensure you have the necessary libraries installed. You can install them using pip:

bash Copy code pip install transformers Usage Here’s an example of how to load and use the model for text generation:

python Copy code from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "your_model_name" # Replace with your model's name

Load model and tokenizer

tokenizer = AutoTokenizer.from_pretrained(model_name) model = AutoModelForCausalLM.from_pretrained(model_name)

Generate text

input_text = "What are the symptoms of diabetes?" input_ids = tokenizer.encode(input_text, return_tensors='pt')

output = model.generate(input_ids, max_length=150) generated_text = tokenizer.decode(output[0], skip_special_tokens=True)

print(generated_text) Limitations The model's output is based on the data it was fine-tuned on and may not always reflect the latest medical guidelines or research. Always verify critical medical information with reliable sources. Contributing If you wish to contribute to this model or report issues, please open an issue on the repository or contact the developer directly.