OpenBioLLM 8B

A biomedical large language model built on Meta’s Llama 3 8B, fine-tuned by Saama AI Labs for medical and clinical question answering. OpenBioLLM is optimized for the biomedical domain and achieves strong results on standard medical benchmarks for its size class.

🚀 Overview

openbiollm packages aaditya/Llama3-OpenBioLLM-8B, an open biomedical language model fine-tuned from Meta-Llama-3-8B. It was developed by Ankit Pal (Aaditya Ura) at Saama AI Labs and trained to specialize in medical, clinical, and biomedical reasoning while retaining the general instruction-following of its Llama 3 base.

• Base model: Meta Llama 3 8B (~8B parameters)
• Context length: 8K tokens
• Domain: Biomedical / clinical question answering
• License: Meta Llama 3 Community License

📊 Benchmarks

Scores reported by the authors across nine biomedical datasets (higher is better). OpenBioLLM-8B is compared against larger proprietary and open models.

Per the authors, OpenBioLLM-8B “demonstrates superior performance compared to larger models, such as GPT-3.5, Meditron-70B across 9 diverse biomedical datasets.” Benchmark numbers are from the official model card; see the HuggingFace page for full methodology.

🎯 Key Features

• Biomedical specialization, fine-tuned for medical, clinical, and life-sciences question answering.
• Strong for its size, competitive with much larger models on standard medical benchmarks.
• Llama 3 foundation, inherits the reasoning and instruction-following of Meta-Llama-3-8B.
• 8K context, handles typical clinical notes, abstracts, and Q&A prompts.
• Drop-in Ollama model, runs locally with a single ollama run command.

🏷️ Available Versions

BPW Reference Guide

💻 Quick Start

CLI

ollama run richardyoung/openbiollm

cURL

curl http://localhost:11434/api/chat -d '{
  "model": "richardyoung/openbiollm",
  "messages": [
    { "role": "user", "content": "What is the mechanism of action of metformin?" }
  ]
}'

Python

import ollama

response = ollama.chat(
    model="richardyoung/openbiollm",
    messages=[{"role": "user", "content": "What is the mechanism of action of metformin?"}],
)
print(response["message"]["content"])

JavaScript

import ollama from "ollama";

const response = await ollama.chat({
  model: "richardyoung/openbiollm",
  messages: [{ role: "user", content: "What is the mechanism of action of metformin?" }],
});
console.log(response.message.content);

🛠️ Use Cases

• Biomedical research, literature exploration, hypothesis generation, and concept lookup.
• Medical education, study aid for students reviewing clinical and life-sciences material.
• Clinical NLP prototyping, entity extraction, summarization, and Q&A over medical text.
• Benchmarking, a strong open baseline for evaluating biomedical LLMs at the 8B scale.

All use cases are for research and educational purposes only, see the Medical Disclaimer below.

📋 System Requirements

CPU-only inference is possible but significantly slower; roughly 10GB of free system RAM is recommended for the Q8_0 quant.

🔧 Technical Details

• Base Model: aaditya/Llama3-OpenBioLLM-8B (fine-tuned from Meta-Llama-3-8B)
• Parameters: ~8B
• Context Length: 8K tokens
• Architecture: Auto-regressive transformer with Grouped-Query Attention (GQA)
• Quantization: Q8_0 (8-bit)
• Domain fine-tuning: Biomedical / clinical (Saama AI Labs)

⚠️ Medical Disclaimer

This model is for research and educational use only. It is NOT a medical device and does NOT provide medical advice.

OpenBioLLM is a language model and its outputs may be inaccurate, incomplete, or misleading. It must not be used for diagnosis, treatment, prescription, triage, or any clinical decision-making. Nothing it produces constitutes professional medical advice, and no doctor-patient relationship is created by its use.

Always consult a qualified healthcare professional for any medical concern. Do not rely on this model in emergencies, contact your local emergency services. The maintainers, base-model authors, and Meta accept no liability for any use of this model in healthcare or clinical settings.

🙏 Acknowledgments

• Base model: Ankit Pal (Aaditya Ura) / Saama AI Labs, OpenBioLLM, fine-tuned from Meta Llama 3.
• Foundation model: Meta, Llama 3 8B.
• Quantization: llama.cpp.

Built & maintained by Richard Young · DeepNeuro