README.md

metadata

language: en
tags:
  - product-recommendation
  - nlp
  - semantic-search
license: mit
datasets:
  - custom

Product Recommendation Model

This model recommends Salesforce org products based on a user query using semantic search. It is trained on a custom dataset of product descriptions and uses a pretrained NLP model (sentence-transformers/all-mpnet-base-v2) to generate recommendations.

Usage

You can use this model via the Hugging Face Inference API or by running the app.py script locally.

Example Query

import requests

API_URL = "https://api-inference.huggingface.co/models/your-username/product-recommendation-model"
headers = {"Authorization": "Bearer YOUR_HUGGING_FACE_TOKEN"}

query = "What products work for telecom?"
response = requests.post(API_URL, headers=headers, json={"query": query, "top_k": 5})

print(response.json())