 Run Request  1. prepare an image.  ```bash !wget https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg ``` 2.run request  ```python import json from typing import List import requests as r import base64  ENDPOINT_URL = "" HF_TOKEN = ""  def predict(path_to_image: str = None):     with open(path_to_image, "rb") as i:         image = i.read()     payload = {         "inputs": [image],         "parameters": {                    "do_sample": True,                    "top_p":0.9,                    "min_length":5,                    "max_length":20         }     }     response = r.post(         ENDPOINT_URL, headers={"Authorization": f"Bearer {HF_TOKEN}"}, json=payload     )     return response.json() prediction = predict(     path_to_image="palace.jpg" )  ``` Example parameters depending on the decoding strategy:  1. Beam search  ```          "parameters": {                    "num_beams":5,                    "max_length":20         } ```  2. Nucleus sampling  ```          "parameters": {                    "num_beams":1,                    "max_length":20,                    "do_sample": True,                    "top_k":50,                    "top_p":0.95         } ```  3. Contrastive search  ```          "parameters": {                    "penalty_alpha":0.6,                    "top_k":4                    "max_length":512         } ```  See [generate()](https://huggingface.co/docs/transformers/v4.25.1/en/main_classes/text_generation