Add initial version of ROBERTA classifier, add ability for multi pi charts

supporting/RAGAS_Service/roberta_service.py

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+from transformers import RobertaTokenizer, RobertaForSequenceClassification
+import torch
+
+MODEL_PATH = "./roberta_classifier"
+
+tokenizer = RobertaTokenizer.from_pretrained(MODEL_PATH)
+model = RobertaForSequenceClassification.from_pretrained(MODEL_PATH)
+
+text2 = "High-profile political downplaying of COVID-19 (examples: President Trump saying 'it will go away' in March–August 2020)"
+text = "Multiple mirrored reuploads (2020–2023) put the clip on other channels with titles implying it was a genuine 1970s public information film."
+
+inputs = tokenizer(
+    text,
+    return_tensors="pt",
+    truncation=True,
+    padding=True
+)
+
+model.eval()
+
+with torch.no_grad():
+    logits = model(**inputs).logits
+
+probs = torch.softmax(logits, dim=1)
+print(probs)