Update app.py

app.py

@@ -1,28 +1,28 @@
 import gradio as gr
 
 models = {
-    # "object-detection": "facebook/detr-resnet-50",
-    "image-classification": "microsoft/resnet-50",
-    "text-to-image": "runwayml/stable-diffusion-v1-5",
-    "image-to-text": "nlpconnect/vit-gpt2-image-captioning",
-    "audio-classification": "mtg-upf/discogs-maest-30s-pw-73e-ts",
-    "audio-to-audio": "speechbrain/mtl-mimic-voicebank",
-    "automatic-speech-recognition": "jonatasgrosman/wav2vec2-large-xlsr-53-english",
-    "conversational": "microsoft/DialoGPT-medium",
-    "feature-extraction": "cambridgeltl/SapBERT-from-PubMedBERT-fulltext",
-    "fill-mask": "bert-base-uncased",
-    "question-answering": "deepset/roberta-base-squad2",
-    "summarization": "facebook/bart-large-cnn",
-    "text-classification": "cardiffnlp/twitter-roberta-base-sentiment-latest",
-    "text-generation": "gpt2",
-    "text2text-generation": "vennify/t5-base-grammar-correction",
-    "translation": "Helsinki-NLP/opus-mt-fr-en",
-    "zero-shot-classification": "facebook/bart-large-mnli",
-    "sentence-similarity": "sentence-transformers/all-mpnet-base-v2",
-    "text-to-speech": "facebook/mms-tts-eng",
-    "token-classification": "benjamin/wtp-canine-s-1l",
-    "document-question-answering": "fxmarty/tiny-doc-qa-vision-encoder-decoder",
-    "visual-question-answering": "Salesforce/blip-vqa-capfilt-large",
+    "object-detection": "facebook/detr-resnet-50",
+    # "image-classification": "microsoft/resnet-50",
+    # "text-to-image": "runwayml/stable-diffusion-v1-5",
+    # "image-to-text": "nlpconnect/vit-gpt2-image-captioning",
+    # "audio-classification": "mtg-upf/discogs-maest-30s-pw-73e-ts",
+    # "audio-to-audio": "speechbrain/mtl-mimic-voicebank",
+    # "automatic-speech-recognition": "jonatasgrosman/wav2vec2-large-xlsr-53-english",
+    # "conversational": "microsoft/DialoGPT-medium",
+    # "feature-extraction": "cambridgeltl/SapBERT-from-PubMedBERT-fulltext",
+    # "fill-mask": "bert-base-uncased",
+    # "question-answering": "deepset/roberta-base-squad2",
+    # "summarization": "facebook/bart-large-cnn",
+    # "text-classification": "cardiffnlp/twitter-roberta-base-sentiment-latest",
+    # "text-generation": "gpt2",
+    # "text2text-generation": "vennify/t5-base-grammar-correction",
+    # "translation": "Helsinki-NLP/opus-mt-fr-en",
+    # "zero-shot-classification": "facebook/bart-large-mnli",
+    # "sentence-similarity": "sentence-transformers/all-mpnet-base-v2",
+    # "text-to-speech": "facebook/mms-tts-eng",
+    # "token-classification": "benjamin/wtp-canine-s-1l",
+    # "document-question-answering": "fxmarty/tiny-doc-qa-vision-encoder-decoder",
+    # "visual-question-answering": "Salesforce/blip-vqa-capfilt-large",
 }
 
 with gr.Blocks() as demo: