lorenzoscottb commited on
Commit
a86e9de
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1 Parent(s): 49f757e

Update app.py

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Files changed (1) hide show
  1. app.py +14 -14
app.py CHANGED
@@ -18,7 +18,7 @@ Three main tasks are available:
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  - Name Entity Recognition (NER), with an English-only model that generates the identified characters.
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- - Sentiment Analysis (SA), with two English-only models (one for classification, one for generation) and a large multilingual model for classification.
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  - Relation Extraction (RE), with an English-only model that identifies relevant characters and existing relations between them following the Activity feature of the Hall and Van de Castle framework.
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@@ -91,12 +91,12 @@ interface_model_S = gr.Interface.load(
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  title="SA Base English-Only",
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  )
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- interface_model_G = gr.Interface.load(
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- name="huggingface/DReAMy-lib/t5-base-DreamBank-Generation-Emot-Char",
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- description=description_G,
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- examples=examples_g,
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- title="SA Generation",
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- )
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  interface_model_RE = gr.Interface.load(
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  name="huggingface/DReAMy-lib/t5-base-DreamBank-Generation-Act-Char",
@@ -113,12 +113,12 @@ interface_model_NER = gr.Interface.load(
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  title="NER Generation",
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  )
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- gr.TabbedInterface(
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- [interface_words, interface_model_L, interface_model_S, interface_model_G, interface_model_RE, interface_model_NER],
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- ["Main", "NER Generation", "SA Large Multilingual", "SA Base En", "SA En Generation", "RE Generation"]
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- ).launch()
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-
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  # gr.TabbedInterface(
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- # [interface_words, interface_model_L, interface_model_S, interface_model_RE, interface_model_NER],
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- # ["Main", "NER Generation", "SA Large Multilingual", "SA Base En", "RE Generation"]
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  # ).launch()
 
 
 
 
 
 
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  - Name Entity Recognition (NER), with an English-only model that generates the identified characters.
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+ - Sentiment Analysis (SA), with one English-only model and a large multilingual model for classification.
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  - Relation Extraction (RE), with an English-only model that identifies relevant characters and existing relations between them following the Activity feature of the Hall and Van de Castle framework.
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  title="SA Base English-Only",
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  )
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+ # interface_model_G = gr.Interface.load(
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+ # name="huggingface/DReAMy-lib/t5-base-DreamBank-Generation-Emot-Char",
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+ # description=description_G,
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+ # examples=examples_g,
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+ # title="SA Generation",
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+ # )
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  interface_model_RE = gr.Interface.load(
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  name="huggingface/DReAMy-lib/t5-base-DreamBank-Generation-Act-Char",
 
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  title="NER Generation",
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  )
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  # gr.TabbedInterface(
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+ # [interface_words, interface_model_L, interface_model_S, interface_model_G, interface_model_RE, interface_model_NER],
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+ # ["Main", "NER Generation", "SA Large Multilingual", "SA Base En", "SA En Generation", "RE Generation"]
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  # ).launch()
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+
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+ gr.TabbedInterface(
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+ [interface_words, interface_model_L, interface_model_S, interface_model_RE, interface_model_NER],
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+ ["Main", "NER Generation", "SA Large Multilingual", "SA Base En", "RE Generation"]
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+ ).launch()