Add application file

app.py

@@ -0,0 +1,27 @@
+import gradio as gr
+
+
+from transformers import AutoModelForSequenceClassification
+import torch
+
+from transformers import AutoTokenizer
+
+
+tokenizer = AutoTokenizer.from_pretrained("Gerard-1705/bertin_base_climate_detection_es")
+
+model = AutoModelForSequenceClassification.from_pretrained("Gerard-1705/bertin_base_climate_detection_es")
+
+id2label = {0: "NEGATIVE", 1: "POSITIVE"}
+label2id = {"NEGATIVE": 0, "POSITIVE": 1}
+
+def inference_fun(user_input):
+    inputs = tokenizer(user_input, return_tensors="pt")
+    with torch.no_grad():
+        logits = model(**inputs).logits
+    predicted_class_id = logits.argmax().item()
+    output_tag = model.config.id2label[predicted_class_id]
+    
+    return output_tag
+
+iface = gr.Interface(fn=inference_fun, inputs="text", outputs="text")
+iface.launch()