metadata

license: apache-2.0
language:
  - en
base_model:
  - lkw99/unsloth-llama-3.1-8b-bnb-4bit
tags:
  - medical
  - biology
  - chemistry
  - text-generation-inference

Vitals GGUF - 16-bit Model

This is the Vitals GGUF - 16-bit model, a finely tuned LLaMA model that has been optimized for efficient medical text generation and healthcare-related applications. The model was trained using Unsloath and Hugging Face's TRL (Transformers Reinforcement Learning) library, resulting in a training process that’s twice as fast as traditional methods.

Model Overview

Developed by: Aviralansh
License: Apache-2.0
Base Model: unsloth/meta-llama-3.1-8b-bnb-4bit
Purpose: This model is designed for AI-driven healthcare solutions, with capabilities in generating accurate medical information, answering healthcare queries, and providing insights related to health and wellness.

This model is hosted on Hugging Face and can be downloaded for use in healthcare applications. It is available in a 16-bit GGUF format, optimized for faster inference without compromising accuracy.

Features

Fast Training: Powered by Unsloath, the model is trained at double the speed compared to standard models.
High-Quality Medical Language Understanding: Ideal for applications requiring high accuracy and consistency in medical responses.
16-Bit Precision: Uses GGUF format to achieve high efficiency in memory usage and faster performance.
Runs on Ollama: Integrates smoothly with the Ollama service, enabling easy deployment and interaction.

How It Works

The Vitals GGUF - 16-bit model is based on the LLaMA architecture, finetuned specifically for the medical domain. The training process incorporated datasets and optimization techniques that make it suitable for healthcare applications, especially where quick response times and detailed medical understanding are essential. This model can be leveraged for applications such as:

Medical Question-Answering: Provides answers to general healthcare and wellness questions.
Symptom Analysis: Helps users interpret symptoms and offers preliminary advice.
Healthcare Data Insights: Analyzes healthcare-related data for trends and insights.

This model, trained with Unsloath, achieved a performance boost by utilizing advanced techniques such as Reinforcement Learning (RL), fine-tuning it for accurate, human-like responses.

Additional Resources

Unsloath: Learn more about Unsloath, a tool that speeds up AI model training.
Hugging Face Model Page: Visit the model on Hugging Face here.

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

Uploaded model

Developed by: Aviralansh
License: apache-2.0
Finetuned from model : unsloth/meta-llama-3.1-8b-bnb-4bit

This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.