--- base_model: unsloth/phi-4-unsloth-bnb-4bit tags: - text-generation-inference - transformers - unsloth - trl - phi - text-generation license: apache-2.0 language: - en --- # 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](https://github.com/unslothai/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: ```bash 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 = "/static-proxy?url=https%3A%2F%2Fapi-inference.huggingface.co%2Fmodels%2FIshika08%2Fphi-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) [](https://github.com/unslothai/unsloth)