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Update README.md

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  1. README.md +3 -4
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@@ -12,7 +12,7 @@ To use deploy this model a an Inference Endpoint you have to select `Custom` as
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  ### expected Request payload
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  ```json
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  {
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- "image": "/9j/4AAQSkZJRgABAQEBLAEsAAD/2wBDAAMCAgICAgMC....", // base64 image as bytes
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  }
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  ```
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  below is an example on how to run a request using Python and `requests`.
@@ -32,7 +32,7 @@ HF_TOKEN = ""
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  def predict(path_to_image: str = None):
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  with open(path_to_image, "rb") as i:
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  b64 = base64.b64encode(i.read())
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- payload = {"inputs": {"image": b64.decode("utf-8")}}
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  response = r.post(
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  ENDPOINT_URL, headers={"Authorization": f"Bearer {HF_TOKEN}"}, json=payload
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  )
@@ -43,11 +43,10 @@ prediction = predict(
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  ```
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  expected output
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  ```python
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- {'feature_vector': [0.016450975090265274,
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  -0.5551009774208069,
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  0.39800673723220825,
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  -0.6809228658676147,
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  2.053842782974243,
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  -0.4712907075881958,...]
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- }
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  ```
 
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  ### expected Request payload
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  ```json
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  {
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+ "inputs": "/9j/4AAQSkZJRgABAQEBLAEsAAD/2wBDAAMCAgICAgMC....", // base64 image as bytes
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  }
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  ```
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  below is an example on how to run a request using Python and `requests`.
 
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  def predict(path_to_image: str = None):
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  with open(path_to_image, "rb") as i:
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  b64 = base64.b64encode(i.read())
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+ payload = {"inputs": b64.decode("utf-8")}
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  response = r.post(
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  ENDPOINT_URL, headers={"Authorization": f"Bearer {HF_TOKEN}"}, json=payload
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  )
 
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  ```
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  expected output
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  ```python
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+ [0.016450975090265274,
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  -0.5551009774208069,
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  0.39800673723220825,
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  -0.6809228658676147,
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  2.053842782974243,
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  -0.4712907075881958,...]
 
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  ```