Spaces:
Running
on
CPU Upgrade
Running
on
CPU Upgrade
update text
Browse files
app.py
CHANGED
|
@@ -40,7 +40,7 @@ def proc_submission(
|
|
| 40 |
token_batch_length (int): the length of the token batches to use
|
| 41 |
length_penalty (float): the length penalty to use
|
| 42 |
repetition_penalty (float): the repetition penalty to use
|
| 43 |
-
no_repeat_ngram_size (int): the no
|
| 44 |
max_input_length (int, optional): the maximum input length to use. Defaults to 1024.
|
| 45 |
|
| 46 |
Returns:
|
|
@@ -166,13 +166,13 @@ if __name__ == "__main__":
|
|
| 166 |
|
| 167 |
gr.Markdown("# Long-Form Summarization: LED & BookSum")
|
| 168 |
gr.Markdown(
|
| 169 |
-
"
|
| 170 |
)
|
| 171 |
with gr.Column():
|
| 172 |
|
| 173 |
gr.Markdown("## Load Inputs & Select Parameters")
|
| 174 |
gr.Markdown(
|
| 175 |
-
"Enter
|
| 176 |
)
|
| 177 |
with gr.Row():
|
| 178 |
model_size = gr.Radio(
|
|
@@ -183,7 +183,7 @@ if __name__ == "__main__":
|
|
| 183 |
label="Beam Search: # of Beams",
|
| 184 |
value=2,
|
| 185 |
)
|
| 186 |
-
gr.Markdown("Load
|
| 187 |
with gr.Row():
|
| 188 |
example_name = gr.Dropdown(
|
| 189 |
_examples,
|
|
@@ -270,7 +270,7 @@ if __name__ == "__main__":
|
|
| 270 |
"- The two most important parameters-empirically-are the `num_beams` and `token_batch_length`. "
|
| 271 |
)
|
| 272 |
gr.Markdown(
|
| 273 |
-
"- The model can be used with tag [pszemraj/led-large-book-summary](https://huggingface.co/pszemraj/led-large-book-summary). See the model card for details on usage & a notebook for a tutorial."
|
| 274 |
)
|
| 275 |
gr.Markdown("---")
|
| 276 |
|
|
|
|
| 40 |
token_batch_length (int): the length of the token batches to use
|
| 41 |
length_penalty (float): the length penalty to use
|
| 42 |
repetition_penalty (float): the repetition penalty to use
|
| 43 |
+
no_repeat_ngram_size (int): the no-repeat ngram size to use
|
| 44 |
max_input_length (int, optional): the maximum input length to use. Defaults to 1024.
|
| 45 |
|
| 46 |
Returns:
|
|
|
|
| 166 |
|
| 167 |
gr.Markdown("# Long-Form Summarization: LED & BookSum")
|
| 168 |
gr.Markdown(
|
| 169 |
+
"LED models ([model card](https://huggingface.co/pszemraj/led-large-book-summary)) fine-tuned to summarize long-form text. A [space with other models can be found here](https://huggingface.co/spaces/pszemraj/document-summarization)"
|
| 170 |
)
|
| 171 |
with gr.Column():
|
| 172 |
|
| 173 |
gr.Markdown("## Load Inputs & Select Parameters")
|
| 174 |
gr.Markdown(
|
| 175 |
+
"Enter or upload text below, and it will be summarized [using the selected parameters](https://huggingface.co/blog/how-to-generate). "
|
| 176 |
)
|
| 177 |
with gr.Row():
|
| 178 |
model_size = gr.Radio(
|
|
|
|
| 183 |
label="Beam Search: # of Beams",
|
| 184 |
value=2,
|
| 185 |
)
|
| 186 |
+
gr.Markdown("Load a a .txt - example or your own (_You may find [this OCR space](https://huggingface.co/spaces/pszemraj/pdf-ocr) useful_)")
|
| 187 |
with gr.Row():
|
| 188 |
example_name = gr.Dropdown(
|
| 189 |
_examples,
|
|
|
|
| 270 |
"- The two most important parameters-empirically-are the `num_beams` and `token_batch_length`. "
|
| 271 |
)
|
| 272 |
gr.Markdown(
|
| 273 |
+
"- The model can be used with tag [pszemraj/led-large-book-summary](https://huggingface.co/pszemraj/led-large-book-summary). See the model card for details on usage & a Colab notebook for a tutorial."
|
| 274 |
)
|
| 275 |
gr.Markdown("---")
|
| 276 |
|