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Update app.py
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app.py
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@@ -56,21 +56,6 @@ GEN_NAMES = [
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"huggingface/EleutherAI/gpt-j-6B",
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"huggingface/gpt2-large"
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]
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GENERATORS = {}
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manager = ModelManager()
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for MODEL_NAME in GEN_NAMES :
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print(f"downloading {MODEL_NAME}")
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model_path, config_path, model_item = manager.download_model(f"{MODEL_NAME}")
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#vocoder_name: Optional[str] = model_item["default_vocoder"]
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#vocoder_path = None
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#vocoder_config_path = None
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#if vocoder_name is not None:
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# vocoder_path, vocoder_config_path, _ = manager.download_model(vocoder_name)
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#synthesizer = Synthesizer(
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# model_path, config_path, None, vocoder_path, vocoder_config_path,
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#)
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#MODELS[MODEL_NAME] = synthesizer
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#ASR
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@@ -81,6 +66,10 @@ def transcribe(audio):
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#Sentiment Classifier
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classifier = pipeline("text-classification")
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#STT
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def speech_to_text(speech):
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text = asr(speech)["text"]
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@@ -91,6 +80,11 @@ def text_to_sentiment(text):
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sentiment = classifier(text)[0]["label"]
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return sentiment
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#Save
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def upsert(text):
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date_time =str(datetime.datetime.today())
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@@ -164,7 +158,7 @@ with demo:
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b3.click(upsert, inputs=text, outputs=saved)
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b4.click(selectall, inputs=text, outputs=savedAll)
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b5.click(tts, inputs=[text,TTSchoice], outputs=audio)
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b6.click(
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# Lets Do It
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demo.launch(share=True)
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@@ -180,9 +174,4 @@ examples = [
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["Collections of people have agency and mass having agency at the mesoscopic level"],
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["Having a deep human connection is an interface problem to solve."],
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["Having a collective creates agency since we build trust in eachother."]
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]
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#gr.Parallel(generator1, generator2, generator3, inputs=gr.inputs.Textbox(lines=5, label="Enter a sentence to get another sentence."),
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# title=title, examples=examples).launch(share=False)
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"huggingface/EleutherAI/gpt-j-6B",
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"huggingface/gpt2-large"
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]
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#ASR
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#Sentiment Classifier
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classifier = pipeline("text-classification")
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# GPT-J: Story Generation Pipeline
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story_gen = pipeline("text-generation", "pranavpsv/gpt2-genre-story-generator")
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#STT
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def speech_to_text(speech):
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text = asr(speech)["text"]
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sentiment = classifier(text)[0]["label"]
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return sentiment
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#TTStory
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def text_to_story(text):
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story= story_gen(text)[0]["label"]
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return story
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#Save
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def upsert(text):
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date_time =str(datetime.datetime.today())
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b3.click(upsert, inputs=text, outputs=saved)
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b4.click(selectall, inputs=text, outputs=savedAll)
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b5.click(tts, inputs=[text,TTSchoice], outputs=audio)
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b6.click(text_to_story, inputs=[text,Storychoice], outputs=text)
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# Lets Do It
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demo.launch(share=True)
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["Collections of people have agency and mass having agency at the mesoscopic level"],
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["Having a deep human connection is an interface problem to solve."],
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["Having a collective creates agency since we build trust in eachother."]
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]
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