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from huggingface_hub import from_pretrained_fastai | |
import gradio as gr | |
from fastai.vision.all import * | |
repo_id = "Ignaciobfp/Practica8-modelo" | |
learner = from_pretrained_fastai(repo_id) | |
labels = ["negative", "positive"] | |
def predict(opinion): | |
pred,pred_idx,probs = learner.predict(opinion) | |
print("coco") | |
return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
# Creamos la interfaz y la lanzamos. | |
gr.Interface(fn=predict, inputs=gr.Textbox(lines=2, placeholder="the movie was neither good or bad"), outputs=gr.outputs.Label(num_top_classes=2), | |
examples=['the movie was utter shit I would rater sting a stick in my eyes than seeing something remotely similar to this again', 'is the best movie i have ever seen, had action, romance, science fiction elements. As fun as movies will ever get']).launch(share=False) |