README.md

elasfar-AI

This repository contains the training code and data for the elasfar-AI model, a personalized assistant for Ibrahim Al-Asfar's portfolio website.

Model Description

The elasfar-AI model is a fine-tuned language model based on Hugging Face Transformers. It is designed to:

• Answer questions related to Ibrahim Al-Asfar's personal portfolio.
• Provide insights about projects (e.g., Mark AI), skills, and professional experience.
• Act as an AI-powered assistant on a personal website.

Intended Use

• Primary Use Case: Interactive Q&A on the portfolio site.
• Audience: Potential employers, collaborators, or visitors.
• Tasks: Question answering and text generation.

Setup

1. Install dependencies: pip install transformers datasets torch huggingface_hub
2. Train the model: python train.py
3. Deploy the backend: node server.js

Training Data

The model is fine-tuned on a custom dataset training_data.csv containing question-answer pairs related to:

• Portfolio content
• Projects
• Skills and professional experience

The dataset is handcrafted to ensure relevant and precise answers.

How to Use (via Hugging Face API)

from huggingface_hub import InferenceClient

client = InferenceClient(token="YOUR_HF_TOKEN")
response = client.text_generation("How the United States was discovered ?", model="ibrahimlasfar/elasfar-AI") 
print(response)