feat: remote-code wrapper so AutoModelForTokenClassification and HallucinationDetector load directly

config.json

@@ -1,8 +1,14 @@
 {
-  "architectures": ["LfmForSpanTagging"],
+  "architectures": ["Lfm2SpanTagger"],
+  "model_type": "lfm2_span_tagger",
+  "auto_map": {
+    "AutoConfig": "modeling_lfm2_span_tagger.Lfm2SpanTaggerConfig",
+    "AutoModelForTokenClassification": "modeling_lfm2_span_tagger.Lfm2SpanTagger"
+  },
   "backbone": "LiquidAI/LFM2.5-Encoder-350M",
+  "classifier_dropout": 0.1,
   "num_labels": 2,
   "id2label": {"0": "supported", "1": "hallucinated"},
   "label2id": {"supported": 0, "hallucinated": 1},
-  "note": "Custom token-classification wrapper; load with the LettuceDetect training script class, see the model card."
+  "torch_dtype": "float32"
 }