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import gradio as gr
from transformers import pipeline
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch
tokenizer = AutoTokenizer.from_pretrained("FuriouslyAsleep/unhappyZebra100")
model = AutoModelForSequenceClassification.from_pretrained("FuriouslyAsleep/unhappyZebra100")
def greet(Doc_Passage_To_Test):
inputs = tokenizer(Doc_Passage_To_Test, return_tensors="pt")
outputs = model(**inputs)
predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)
#print(predictions)
# return "Hello " + name + "!!"
return "Probabilities are listed here (False prob, then True prob): " + str(predictions)
iface = gr.Interface(fn=greet, inputs="text", outputs="text")
iface.launch()
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