feat(model): ajoute le modèle CamemBERT fine-tuné avec renommage des labels

models/fine_tuned.py

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+from transformers import CamembertTokenizer, CamembertForSequenceClassification
+import torch
+
+class FineTunedModel:
+    def __init__(self):
+        model_id = "ymokay/toxicheck-camembert"
+        self.tokenizer = CamembertTokenizer.from_pretrained(model_id)
+        self.model = CamembertForSequenceClassification.from_pretrained(model_id)
+        self.model.eval()
+        self.label_map = {
+            "LABEL_0": "non-toxique",
+            "LABEL_1": "toxique"
+        }
+
+    def predict(self, text: str):
+        inputs = self.tokenizer(text, return_tensors="pt", truncation=True, padding=True)
+        with torch.no_grad():
+            logits = self.model(**inputs).logits
+            probs = torch.softmax(logits, dim=1).squeeze()
+
+        labels = [self.label_map.get(self.model.config.id2label[i], self.model.config.id2label[i]) for i in range(len(probs))]
+        return [(label, float(probs[i])) for i, label in enumerate(labels)]