readme: ---
  language: 
  - en
  - fr
  - ro
  - de
  datasets:
  - c4
  tags:
  - text2text-generation
  - endpoints-template
  license: apache-2.0
  ---
  
  # Fork of [t5-11b](https://huggingface.co/t5-11b)
  
  > This is fork of [t5-11b](https://huggingface.co/t5-11b) implementing a custom `handler.py` as an example for how to use `t5-11b` with [inference-endpoints](https://hf.co/inference-endpoints) on a single NVIDIA T4.
  
  --- 
  
  # Model Card for T5 11B - fp16
  
  ![model image](https://camo.githubusercontent.com/623b4dea0b653f2ad3f36c71ebfe749a677ac0a1/68747470733a2f2f6d69726f2e6d656469756d2e636f6d2f6d61782f343030362f312a44304a31674e51663876727255704b657944387750412e706e67)
  
  # Use with Inference Endpoints 
  
  Hugging Face Inference endpoints can be used with an HTTP client in any language. We will use Python and the `requests` library to send our requests. (make your you have it installed `pip install requests`)
  
  ![result](inference.png)
  
  ## Send requests with Pyton
  
  ```python
  import json
  import requests as r
  
  ENDPOINT_URL=""# url of your endpoint
  HF_TOKEN=""
  
  # payload samples
  regular_payload = { "inputs": "translate English to German: The weather is nice today." }
  parameter_payload = {
  	"inputs": "translate English to German: Hello my name is Philipp and I am a Technical Leader at Hugging Face",
    "parameters" : {
      "max_length": 40,
    }
  }
  
  # HTTP headers for authorization
  headers= {
      "Authorization": f"Bearer {HF_TOKEN}",
      "Content-Type": "application/json"
  }
  
  # send request
  response = r.post(ENDPOINT_URL, headers=headers, json=paramter_payload)
  generated_text = response.json()
  
  print(generated_text)
  
  ```
  