metadata

base_model: unsloth/meta-llama-3.1-8b-bnb-4bit
language:
  - en
license: apache-2.0
tags:
  - text-generation-inference
  - transformers
  - unsloth
  - llama
  - trl
  - sft

Model README

Model Overview

Model Name: Medicine_chat
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:

pip install transformers
## Usage

Here’s an example of how to load and use the model for text generation:

```python
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)