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6e7c730
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Add application file

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  1. app.py +34 -0
app.py ADDED
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+ import gradio as gr
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+
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+ models = {
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+ # "object-detection": "facebook/detr-resnet-50",
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+ "image-classification": "microsoft/resnet-50",
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+ "text-to-image": "cagliostrolab/animagine-xl-3.0",
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+ "image-to-text": "Salesforce/blip-image-captioning-large",
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+ "audio-classification": "speechbrain/emotion-recognition-wav2vec2-IEMOCAP",
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+ "audio-to-audio": "speechbrain/mtl-mimic-voicebank",
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+ "automatic-speech-recognition": "jonatasgrosman/wav2vec2-large-xlsr-53-english",
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+ "conversational": "microsoft/DialoGPT-medium",
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+ "feature-extraction": "cambridgeltl/SapBERT-from-PubMedBERT-fulltext",
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+ "fill-mask": "bert-base-uncased",
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+ "question-answering": "deepset/roberta-base-squad2",
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+ "summarization": "facebook/bart-large-cnn",
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+ "text-classification": "cardiffnlp/twitter-roberta-base-sentiment-latest",
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+ "text-generation": "gpt2",
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+ "text2text-generation": "vennify/t5-base-grammar-correction",
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+ "translation": "Helsinki-NLP/opus-mt-fr-en",
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+ "zero-shot-classification": "facebook/bart-large-mnli",
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+ "sentence-similarity": "sentence-transformers/all-mpnet-base-v2",
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+ "text-to-speech": "facebook/mms-tts-eng",
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+ "token-classification": "benjamin/wtp-canine-s-1l",
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+ "document-question-answering": "fxmarty/tiny-doc-qa-vision-encoder-decoder",
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+ "visual-question-answering": "Salesforce/blip-vqa-capfilt-large",
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+ }
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+
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+ with gr.Blocks() as demo:
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+ gr.Markdown("## Gradio Pipelines Tasks")
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+ for k, v in models.items():
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+ with gr.Tab(k):
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+ gr.load(v, src="models")
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+ demo.launch()
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+