llamafile medical biology text-generation fr en de nl es pt pl ro it dataset:pubmed license:apache-2.0 region:us
---
license: apache-2.0
datasets:
- pubmed
language:
- fr
- en
- de
- nl
- es
- pt
- pl
- ro
- it
pipeline_tag: text-generation
gguf_version_by: MaziyarPanahi
llamafile coverted by : Shaikat
tags:
- medical
- biology
---

This repo contains llamafile version for BioMistral-7B model. This llamafile is created from gguf format of original model's quantized version. 

## GGUF version

The gguf version of the  model is created by [ MaziyarPanahi](https://huggingface.co/MaziyarPanahi/BioMistral-7B-GGUF).  Thank you very much for gguf version.

# About llamafile

llamafile is the new framework that collapses all the complexity of (large language models) LLMs down to a single-file executable (called a "llamafile") that runs locally on most computers, with no installation. The first release of llamafile is a product of Mozilla’s innovation group and developed by [Justine Tunney](https://justine.lol/), about llamafile in short as per [introductory post](https://hacks.mozilla.org/2023/11/introducing-llamafile/)

**llamafile lets you turn large language model (LLM) weights into executables.**

**Say you have a set of LLM weights in the form of a 4GB file (in the commonly-used GGUF format). With llamafile you can transform that 4GB file into a binary that runs on six OSes without needing to be installed.**

Basically, llamafile lets anyone distribute and run LLMs with a single file.

Here in [github](https://github.com/Mozilla-Ocho/llamafile/issues/242#issuecomment-1930700064) you can find how I created llamafile version from gguf version for other model. 

## [From the original model card ](https://huggingface.co/BioMistral/BioMistral-7B/)

Large Language Models (LLMs) have demonstrated remarkable versatility in recent years, offering potential applications across specialized domains such as healthcare and medicine. Despite the availability of various open-source LLMs tailored for health contexts, adapting general-purpose LLMs to the medical domain presents significant challenges.
In this paper, we introduce BioMistral, an open-source LLM tailored for the biomedical domain, utilizing Mistral as its foundation model and further pre-trained on PubMed Central. We conduct a comprehensive evaluation of BioMistral on a benchmark comprising 10 established medical question-answering (QA) tasks in English. We also explore lightweight models obtained through quantization and model merging approaches. Our results demonstrate BioMistral's superior performance compared to existing open-source medical models and its competitive edge against proprietary counterparts. Finally, to address the limited availability of data beyond English and to assess the multilingual generalization of medical LLMs, we automatically translated and evaluated this benchmark into 7 other languages. This marks the first large-scale multilingual evaluation of LLMs in the medical domain. Datasets, multilingual evaluation benchmarks, scripts, and all the models obtained during our experiments are freely released.

**Advisory Notice!** Although BioMistral is intended to encapsulate medical knowledge sourced from high-quality evidence, it hasn't been tailored to effectively, safely, or suitably convey this knowledge within professional parameters for action. We advise refraining from utilizing BioMistral in medical contexts unless it undergoes thorough alignment with specific use cases and undergoes further testing, notably including randomized controlled trials in real-world medical environments. BioMistral 7B may possess inherent risks and biases that have not yet been thoroughly assessed. Additionally, the model's performance has not been evaluated in real-world clinical settings. Consequently, we recommend using BioMistral 7B strictly as a research tool and advise against deploying it in production environments for natural language generation or any professional health and medical purposes.

# BioMistral models

**BioMistral** is a suite of Mistral-based further pre-trained open source models suited for the medical domains and pre-trained using textual data from PubMed Central Open Access (CC0, CC BY, CC BY-SA, and CC BY-ND). All the models are trained using the CNRS (French National Centre for Scientific Research) [Jean Zay](http://www.idris.fr/jean-zay/) French HPC.

|      Model Name     |             Base Model             |      Model Type     | Sequence Length |                          Download                          |
|:-------------------:|:----------------------------------:|:-------------------:|:---------------:|:-----------------------------------------------------:|
|    BioMistral-7B    | [Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) | Further Pre-trained |       2048      |    [HuggingFace](https://huggingface.co/BioMistral/BioMistral-7B)    |


# How to run the llamafile version

To run llamafile version in windows just rename the file by adding .exe at the last and run it as you run any other exe file. 

For running in linux run like any binary in linux, just make sure the llamafile is executable by running chmod. 

Thats it. 

 Thank you for using this model.