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from huggingface_hub import from_pretrained_fastai | |
import gradio as gr | |
from fastai.vision.all import * | |
# repo_id = "YOUR_USERNAME/YOUR_LEARNER_NAME" | |
repo_id = "rodrigomiranda98/tweet-eval-emotion" | |
learner = from_pretrained_fastai(repo_id) | |
labels = ['anger', 'joy', 'optimism', 'sadness'] | |
# Definimos una función que se encarga de llevar a cabo las predicciones | |
def predict(text): | |
pred, pred_idx, probs = learner.predict(text) | |
print(f'pred: {pred}') | |
print(f'probs: {probs}') | |
return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
# Creamos la interfaz y la lanzamos. | |
gr.Interface( | |
fn=predict, | |
inputs=gr.inputs.Textbox(lines=5, placeholder="Inserta el texto aquí"), | |
outputs=gr.outputs.Label(num_top_classes=4), | |
examples=["Everything will be fine, you'll see!", "My favorite team did not qualify, I'm sad."] | |
).launch(share=False) |