Felix Marty commited on
Commit
93aa084
β€’
1 Parent(s): 210777d

better with two cols?

Browse files
Files changed (1) hide show
  1. app.py +9 -8
app.py CHANGED
@@ -92,7 +92,9 @@ TITLE = """
92
  # for some reason https://huggingface.co/settings/tokens is not showing as a link by default?
93
  DESCRIPTION = """
94
  This Space allows to automatically convert to ONNX πŸ€— transformers PyTorch models hosted on the Hugging Face Hub. It opens a PR on the target model, and it is up to the owner of the original model
95
- to merge the PR to allow people to leverage the ONNX standard to share and use the model on a wide range of devices! Once converted, the model can for example be used in the [πŸ€— Optimum](https://huggingface.co/docs/optimum/) library following closely the transormers API.
 
 
96
  Check out [this guide](https://huggingface.co/docs/optimum/main/en/onnxruntime/usage_guides/models) to see how!
97
 
98
  The steps are the following:
@@ -100,12 +102,15 @@ The steps are the following:
100
  - Input a model id from the Hub (for example: [textattack/distilbert-base-cased-CoLA](https://huggingface.co/textattack/distilbert-base-cased-CoLA))
101
  - Click "Convert to ONNX"
102
  - That's it! You'll get feedback if it works or not, and if it worked, you'll get the URL of the opened PR!
 
 
103
  """
104
 
105
  with gr.Blocks() as demo:
106
- gr.HTML(TTILE_IMAGE)
107
- gr.HTML(TITLE)
108
- gr.Markdown(DESCRIPTION)
 
109
 
110
  with gr.Column():
111
  input_token = gr.Textbox(max_lines=1, label="Hugging Face token")
@@ -123,10 +128,6 @@ with gr.Blocks() as demo:
123
  btn = gr.Button("Convert to ONNX")
124
  output = gr.Markdown(label="Output")
125
 
126
- gr.Markdown("""
127
- Note: in case the model to convert is larger than 2 GB, it will be saved in a subfolder called `onnx/`. To load it from Optimum, the argument `subfolder="onnx"` should be provided.
128
- """)
129
-
130
  btn.click(
131
  fn=onnx_export, inputs=[input_token, input_model, input_task], outputs=output
132
  )
 
92
  # for some reason https://huggingface.co/settings/tokens is not showing as a link by default?
93
  DESCRIPTION = """
94
  This Space allows to automatically convert to ONNX πŸ€— transformers PyTorch models hosted on the Hugging Face Hub. It opens a PR on the target model, and it is up to the owner of the original model
95
+ to merge the PR to allow people to leverage the ONNX standard to share and use the model on a wide range of devices!
96
+
97
+ Once converted, the model can for example be used in the [πŸ€— Optimum](https://huggingface.co/docs/optimum/) library following closely the transormers API.
98
  Check out [this guide](https://huggingface.co/docs/optimum/main/en/onnxruntime/usage_guides/models) to see how!
99
 
100
  The steps are the following:
 
102
  - Input a model id from the Hub (for example: [textattack/distilbert-base-cased-CoLA](https://huggingface.co/textattack/distilbert-base-cased-CoLA))
103
  - Click "Convert to ONNX"
104
  - That's it! You'll get feedback if it works or not, and if it worked, you'll get the URL of the opened PR!
105
+
106
+ Note: in case the model to convert is larger than 2 GB, it will be saved in a subfolder called `onnx/`. To load it from Optimum, the argument `subfolder="onnx"` should be provided.
107
  """
108
 
109
  with gr.Blocks() as demo:
110
+ with gr.Column():
111
+ gr.HTML(TTILE_IMAGE)
112
+ gr.HTML(TITLE)
113
+ gr.Markdown(DESCRIPTION)
114
 
115
  with gr.Column():
116
  input_token = gr.Textbox(max_lines=1, label="Hugging Face token")
 
128
  btn = gr.Button("Convert to ONNX")
129
  output = gr.Markdown(label="Output")
130
 
 
 
 
 
131
  btn.click(
132
  fn=onnx_export, inputs=[input_token, input_model, input_task], outputs=output
133
  )