Llama-2-7b-chat-finetune Open-source Medical Dialogue Model - Free Q&A Providing Professional Medical Knowledge

Llama 2 7b Chat Finetune

Developed by SURESHBEEKHANI

A medical dialogue model fine-tuned based on Llama-2-7b, designed to answer medical-related questions and provide detailed knowledge.

Large Language Model

Transformers

EnglishOpen Source License:MIT #Medical Q&A #Llama-2 fine-tuning #Professional term analysis

Downloads 16

Release Time : 1/14/2025

Model Overview

This model is a fine-tuned version of Llama-2-7b, specifically designed for medical chat applications, capable of generating detailed text responses related to medical topics.

Model Features

Professional medical dialogue

Fine-tuned for the medical field, capable of generating professional and detailed medical knowledge responses.

Based on Llama-2 architecture

Fine-tuned from the powerful Llama-2-7b model, inheriting its excellent language understanding and generation capabilities.

Conversational style optimization

Designed specifically for chat applications, capable of generating natural and fluent text in a conversational style.

Model Capabilities

Medical knowledge Q&A

Professional term explanation

Medical text generation

Use Cases

Medical assistance

Medical knowledge query

Answer users' professional questions about medical concepts, disease symptoms, treatment methods, etc.

Provide detailed and accurate medical knowledge explanations.

Medical terminology explanation

Help non-professionals understand complex medical terms and concepts.

Generate easy-to-understand terminology explanations.

Medical education

Medical learning aid

Serve as a learning aid tool for medical students or practitioners, providing relevant knowledge references.

Help users quickly acquire medical knowledge.

🚀 Llama-2-7b-chat-finetune

This model is a fine - tuned version of Llama - 2 - 7b for chat - based applications. It is trained on medical data to answer various queries with detailed medical knowledge.

🚀 Quick Start

Use the code below to get started with the model.

Basic Usage

from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer

model_name = "SURESHBEEKHANI/Llama-2-7b-chat-finetune"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

prompt = " What is Superficial vein thrombosis and explain in detail? ?"
pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer, max_length=200)
result = pipe(f"<s>[INST] {prompt} [/INST]")
print(result[0]['generated_text'])

✨ Features

This model is fine - tuned from Llama - 2 - 7b for answering medical - related queries and tasks using a large corpus of medical data.
It is suitable for generating text based on a given prompt in a conversational style.
It can be used directly for generating text responses to prompts related to medical topics and assist in answering medical queries with detailed information.

📚 Documentation

Model Details

Model Description

This model is fine - tuned from Llama - 2 - 7b for answering medical - related queries and tasks using a large corpus of medical data. It is suitable for generating text based on a given prompt in a conversational style.

Property	Details
Developed by	SURESHBEEKHANI
License	MIT
Model Type	Causal Language Model
Language(s)	English
Finetuned from model	Llama - 2 - 7b

Model Sources

Repository: SURESHBEEKHANI/Llama-2-7b-chat-finetune
Code Notebook: Fine - tune Llama - 2 - 7b

Use Cases

Direct Use

This model can be used directly for generating text responses to prompts related to medical topics. It is designed to assist in answering medical queries with detailed information.

Out - of - Scope Use

This model is not suitable for generating answers related to non - medical domains, and should not be used in contexts where the data might be sensitive, harmful, or biased.

Bias, Risks, and Limitations

The model might inherit biases from its training data and might not always provide accurate medical information. It is recommended to use the model as a supplementary tool and consult medical professionals for critical use cases.

📄 License

This model is released under the MIT license.

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