Add fine-tuned EuroBERT for binary geopolitical classification

README.md

@@ -36,14 +36,15 @@ Fine-tuned `EuroBERT/EuroBERT-210m` for **binary** classification of geopolitica
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch
 
-model_id = "durrani95/eurobert-geopolitical-binary"
+model_id = "Durrani95/eurobert-geopolitical-binary"
 
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForSequenceClassification.from_pretrained(model_id)
 
 texts = [
-    "The EU imposed sanctions amid growing tensions with Russia.",
-    "New trade agreements are boosting European exports."
+    "“Energy Sanctions Deepen Divide Between Western Bloc and Major Oil Exporters.",
+    "Military Exercises Near Disputed Waters Raise Fears of Regional Escalations.",
+
 ]
 
 inputs = tokenizer(texts, padding=True, truncation=True, max_length=3200, return_tensors="pt")
@@ -59,19 +60,6 @@ for text, p in zip(texts, probs):
     print(f"{label:>16}  {confidence:6.2%}  | {text}")
 ```
 
-### Inference API (no local setup)
-
-```python
-from huggingface_hub import InferenceClient
-
-client = InferenceClient(model="durrani95/eurobert-geopolitical-binary")  # add token=... if private
-res = client.text_classification("Parliament passed emergency measures amid escalating border tensions.")
-print(res)  # [{'label': 'geopolitical', 'score': 0.99}, ...]
-```
-
-```bash
-curl https://api-inference.huggingface.co/models/durrani95/eurobert-geopolitical-binary   -H "Authorization: Bearer $HF_TOKEN"   -X POST -d '{"inputs": "Talks broke down at the UN Security Council."}'
-```
 
 ---