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lorenzoscottb
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a86e9de
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Parent(s):
49f757e
Update app.py
Browse files
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
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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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)
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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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@@ -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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# 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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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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