Add model card and usage instructions

README.md

@@ -80,6 +80,24 @@ The API returns L1/L2/fusion scores, the selected label and the view count.
 Loading the model does not download external weights after this repository
 has been downloaded. It uses `backbones/ViT-L-14.pt`.
 
+## Run the web demo locally
+
+The tested Gradio UI is included in `demo/`. From the downloaded model directory:
+
+```bash
+python -m pip install -r demo/requirements.txt
+LTF_MODEL_DIR="$PWD" python demo/app.py
+```
+
+Open `http://localhost:7860`. For a remote server, forward port 7860 over SSH.
+Upload an original file, click **Detect**, and inspect fusion, L1 and L2 scores.
+The preview is for display only; inference uses the original file's bytes.
+
+The demo also supports deployment as a separate Gradio Space. Set
+`LTF_MODEL_REPO` to this model ID and `LTF_MODEL_REVISION` to a commit SHA.
+Creating the online compute Space requires an eligible Hugging Face account.
+Publishing the model repository alone does not start a hosted inference service.
+
 ## Checkpoint identity and provenance
 
 `weights/epoch_20.pth` is the original core state_dict (not `best.pth`):