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86a73fe 4b2a1b4 86a73fe 4b2a1b4 86a73fe 4b2a1b4 86a73fe 4b2a1b4 74a3aa1 86a73fe 74a3aa1 86a73fe 4b2a1b4 74a3aa1 4b2a1b4 86a73fe | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 | import torch
import gradio as gr
from transformers import AutoTokenizer, AutoModelForSequenceClassification
MODEL_NAME = "duclo90/Semeval"
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
model = AutoModelForSequenceClassification.from_pretrained(MODEL_NAME)
model.eval()
def classify_text(text):
if not text.strip():
return "Please enter some text."
inputs = tokenizer(
text,
return_tensors="pt",
truncation=True,
padding=True,
max_length=512,
)
with torch.no_grad():
logits = model(**inputs).logits
probs = torch.softmax(logits, dim=-1)
pred_id = torch.argmax(probs, dim=1).item()
label = model.config.id2label[pred_id]
confidence = round(probs[0][pred_id].item(), 3)
return f"Prediction: {label} (Confidence: {confidence})"
iface = gr.Interface(
fn=classify_text,
inputs=gr.Textbox(lines=6),
outputs="text",
title="Human vs Machine Text Classifier",
)
iface.launch()
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