Update README.md

README.md

@@ -22,3 +22,45 @@ license: apache-2.0   # เปลี่ยนได้ตามที่คุ
 ---
 
 ## โครงไฟล์
+common/models.py # สร้างโมเดลด้วย create_model_by_name(...)
+baseline/config.json
+baseline/model.safetensors
+cnn_bilstm/config.json
+cnn_bilstm/model.safetensors
+
+
+## วิธีใช้งานอย่างรวดเร็ว
+
+> ต้องมี `torch`, `transformers`, `safetensors`, `sentencepiece`
+
+```python
+import json, importlib.util, torch, torch.nn.functional as F
+from transformers import AutoTokenizer
+from huggingface_hub import hf_hub_download
+from safetensors.torch import load_file
+
+REPO_ID   = "Dusit-P/thai-sentiment-wcb"
+MODEL_DIR = "cnn_bilstm"    # หรือ "baseline"
+
+# โหลดสถาปัตยกรรม
+models_py = hf_hub_download(REPO_ID, filename="common/models.py")
+spec = importlib.util.spec_from_file_location("models", models_py)
+mod = importlib.util.module_from_spec(spec); spec.loader.exec_module(mod)
+
+# โหลดคอนฟิกและน้ำหนัก
+cfg_path = hf_hub_download(REPO_ID, filename=f"{MODEL_DIR}/config.json")
+w_path   = hf_hub_download(REPO_ID, filename=f"{MODEL_DIR}/model.safetensors")
+cfg = json.load(open(cfg_path, "r", encoding="utf-8"))
+
+tok = AutoTokenizer.from_pretrained(cfg["base_model"])
+model = mod.create_model_by_name(cfg["arch"])
+state = load_file(w_path)
+model.load_state_dict(state, strict=True)
+model.eval()
+
+text = "บริการดีมาก ประทับใจ"
+enc = tok([text], padding=True, truncation=True, max_length=cfg["max_len"], return_tensors="pt")
+with torch.no_grad():
+    p = F.softmax(model(enc["input_ids"], enc["attention_mask"]), dim=1)[0].tolist()
+
+print({"negative": p[0], "positive": p[1], "label": "positive" if p[1] >= p[0] else "negative"})