inital

t5_large/app.py

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+import gradio as gr
+
+from transformers import T5Tokenizer, T5Model
+
+def inference(text):
+    model_path = "t5-large"
+    tokenizer = T5Tokenizer.from_pretrained(model_path)
+    model = T5Model.from_pretrained(model_path)
+
+    input_ids = tokenizer(
+        text, return_tensors="pt"
+    ).input_ids  # Batch size 1
+    decoder_input_ids = tokenizer("Studies show that", return_tensors="pt").input_ids  # Batch size 1
+
+    # forward pass
+    outputs = model(input_ids=input_ids, decoder_input_ids=decoder_input_ids)
+
+    print(outputs[0])
+    last_hidden_states = outputs.last_hidden_state
+    return outputs[0]
+
+examples=[["Studies have been shown that owning a dog is good for you"]]
+
+with gr.Blocks() as demo:
+    gr.Markdown(
+    """
+    # Translation:t5-large
+    Gradio Demo for t5-large. To use it, simply type in text, or click one of the examples to load them.
+    """)
+    with gr.Row():
+        text_input = gr.Textbox()
+        text_output = gr.Textbox()
+    image_button = gr.Button("上传")
+    image_button.click(inference, inputs=text_input, outputs=text_output)
+    gr.Examples(examples,inputs=text_input)
+
+demo.launch()

t5_large/t5-large

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+Subproject commit 6ed159b7a9408621a1ed0b9ca39aacc42c694d73