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README.md

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+---
+license: mit
+tags:
+  - multimodal
+  - emotion-recognition
+  - ambivalence
+  - hesitancy
+  - ABAW10
+---
+
+# ConflictAwareAH — Ambivalence/Hesitancy Recognition
+
+Pre-trained weights for the Conflict-Aware Multimodal Fusion model (ABAW10 Challenge, AVGF1 0.715).
+
+## Usage
+
+```python
+import torch
+from bah.models import ConflictAwareAHModel
+from huggingface_hub import hf_hub_download
+
+ckpt_path = hf_hub_download(repo_id="Bekhouche/ConflictAwareAH", filename="best_model.pt")
+ckpt = torch.load(ckpt_path, map_location="cpu")
+args = ckpt["args"]
+
+# Infer fusion_type from checkpoint keys
+state_keys = set(ckpt["model"].keys())
+fusion_type = args.get("fusion_type") or ("6token" if any("fusion_transformer" in k for k in state_keys) else "concat")
+
+model = ConflictAwareAHModel(
+    video_model=args["video_model"],
+    audio_model=args["audio_model"],
+    text_model=args["text_model"],
+    dropout=0.0,
+    freeze_encoders=args.get("freeze_encoders", True),
+    unfreeze_top_k=args.get("unfreeze_top_k", 0),
+    num_transformer_layers=args.get("num_layers", 2),
+    fusion_type=fusion_type,
+)
+model.load_state_dict(ckpt["model"], strict=True)
+model.eval()
+
+text_blend = ckpt.get("text_blend", args.get("text_blend", 0.5))
+```
+
+## Config
+
+- Encoders: VideoMAE-Base, HuBERT-Base, RoBERTa-GoEmotions (frozen)
+- Dropout: 0.4
+- Text blend (inference): 0.5