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#!/usr/bin/env python
# coding: utf-8
# In[2]:
import gradio as gr
import torch
# In[3]:
model_ckpt = "langfab/distilbert-base-uncased-finetuned-movie-genre"
from transformers import (AutoTokenizer, AutoConfig,
AutoModelForSequenceClassification)
tokenizer = AutoTokenizer.from_pretrained(model_ckpt)
config = AutoConfig.from_pretrained(model_ckpt)
model = AutoModelForSequenceClassification.from_pretrained(model_ckpt,config=config)
# In[4]:
id2label = model.config.id2label
def predict(plot):
encoding = tokenizer(plot, padding=True, truncation=True, return_tensors="pt")
encoding = {k: v.to(model.device) for k,v in encoding.items()}
outputs = model(**encoding)
logits = outputs.logits
logits.shape
predictions = torch.nn.functional.softmax(logits.squeeze().cpu(), dim=-1)
predictions
return id2label[int(predictions.argmax())]
iface = gr.Interface(title = "Movie Plot Genre Predictor", fn=predict, inputs="text", outputs="text")
iface.launch(share=True)
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