Llama3-Aloe-8B-Alpha-GGUF Open-source Model - Free Support for Knowledge Q&A in Biology and Medicine Fields

Llama3 Aloe 8B Alpha GGUF

Developed by tensorblock

Llama3-Aloe-8B-Alpha is an 8B parameter large language model focused on the fields of biology and medicine, offering a quantized version in GGUF format

Large Language Model

Transformers

English#Biomedical Q&A #Multi-dataset training #GGUF quantization

Downloads 224

Release Time : 11/8/2024

Model Overview

A domain-specific model based on the Llama3 architecture, optimized for biology and medicine Q&A tasks, supporting multiple quantized versions to meet different hardware requirements

Model Features

Domain targeting

Specifically optimized for the fields of biology and medicine, performing excellently in relevant Q&A tasks

Multi-dataset training

Trained using multiple high-quality datasets such as argilla/dpo-mix-7k and nvidia/HelpSteer

Multiple quantized versions

Offers a total of 12 quantized versions from Q2_K to Q8_0 to adapt to different hardware and performance requirements

llama.cpp compatibility

All model files in GGUF format are fully compatible with the latest version of llama.cpp

Model Capabilities

Biology domain Q&A

Medicine domain Q&A

Professional domain text generation

Multi-round dialogue

Use Cases

Medical health

Medical question answering

Answer professional medical questions raised by patients or medical students

Provide accurate and reliable medical information

Medical literature understanding

Assist researchers in understanding and summarizing the content of medical literature

Improve the efficiency of literature reading

Biological research

Biological concept explanation

Explain complex biological concepts and terms

Help students and researchers quickly understand professional knowledge

Experimental protocol suggestion

Provide preliminary protocol suggestions for biological experiments

Assist in the experimental design process

🚀 HPAI-BSC/Llama3-Aloe-8B-Alpha - GGUF

This repository offers GGUF format model files for HPAI-BSC/Llama3-Aloe-8B-Alpha. These files are quantized using machines provided by TensorBlock, and are compatible with llama.cpp as of commit b4011.

✨ Features

Diverse Datasets: Trained on a wide range of datasets including argilla/dpo-mix-7k, nvidia/HelpSteer, jondurbin/airoboros-3.2, etc.
Multiple Tags: Tags such as biology, medical, TensorBlock, and GGUF highlight its application areas.
Question Answering: Designed for the question-answering pipeline.

📦 Installation

Command line

Install Huggingface Client:

pip install -U "huggingface_hub[cli]"

Download the individual model file to a local directory:

huggingface-cli download tensorblock/Llama3-Aloe-8B-Alpha-GGUF --include "Llama3-Aloe-8B-Alpha-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you want to download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/Llama3-Aloe-8B-Alpha-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'

📚 Documentation

Our projects

Project Name	Description	Image	Link
Awesome MCP Servers	A comprehensive collection of Model Context Protocol (MCP) servers.		See what we built
TensorBlock Studio	A lightweight, open, and extensible multi-LLM interaction studio.		See what we built

Prompt template

<|begin_of_text|><|start_header_id|>system<|end_header_id|>

{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>

{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>

Model file specification

Property	Details
Model Type	GGUF format model files for HPAI-BSC/Llama3-Aloe-8B-Alpha
Training Data	argilla/dpo-mix-7k, nvidia/HelpSteer, jondurbin/airoboros-3.2, hkust-nlp/deita-10k-v0, LDJnr/Capybara, HPAI-BSC/CareQA, GBaker/MedQA-USMLE-4-options, lukaemon/mmlu, bigbio/pubmed_qa, openlifescienceai/medmcqa, bigbio/med_qa, HPAI-BSC/better-safe-than-sorry, HPAI-BSC/pubmedqa-cot, HPAI-BSC/medmcqa-cot, HPAI-BSC/medqa-cot
Filename	Llama3-Aloe-8B-Alpha-Q2_K.gguf, Llama3-Aloe-8B-Alpha-Q3_K_S.gguf, etc.
Quant type	Q2_K, Q3_K_S, Q3_K_M, etc.
File Size	2.961 GB, 3.413 GB, 3.743 GB, etc.
Description	smallest, significant quality loss - not recommended for most purposes; very small, high quality loss; etc.

📄 License

This project is licensed under the cc-by-nc-4.0 license.

Featured Recommended AI Models

Empowering the Future, Your AI Solution Knowledge Base

English 简体中文繁體中文にほんご