Ishika08/phi-4_fine-tuned_mdl

Uploaded model

• Developed by: Ishika08
• License: apache-2.0
• Finetuned from model : unsloth/phi-4-unsloth-bnb-4bit

This phi model was trained 2x faster with Unsloth and Huggingface's TRL library.

How to Use the Model for Inferencing

You can use the model for inferencing via Hugging Face's API by following the steps below:

1. Install Required Libraries

Ensure that you have the requests library installed:

pip install requests

Steps to use the model for inferencing using Hugging Face API

import requests

API URL for the model hosted on Hugging Face

API_URL = "https://api-inference.huggingface.co/models/Ishika08/phi-4_fine-tuned_mdl"

Set up your Hugging Face API token

HEADERS = {"Authorization": f"Bearer token_id"}

The input you want to pass to the model

payload = { "inputs": "What is the capital of France? Tell me some of the tourist places in bullet points." }

Make the request to the API

response = requests.post(API_URL, headers=HEADERS, json=payload)

Print the response from the model

print(response.json()) # Get the response output

OUTPUT

{ "generated_text": "Paris is the capital of France. Some of the famous tourist places include:\n- Eiffel Tower\n- Louvre Museum\n- Notre-Dame Cathedral\n- Sacré-Cœur Basilica" }

Steps to use model using InferenceClient library from huggingface_hub

from huggingface_hub import InferenceClient

Initialize the client with model name and Hugging Face token

client = InferenceClient(model="Ishika08/phi-4_fine-tuned_mdl", token=""")

Perform inference (text generation in this case)

response = client.text_generation("What is the capital of France? Tell me about Eiffel Tower history in bullet points.")

Print the response from the model

print(response)